Mathematical morphology-based shape feature analysis for Chinese character recognition systems

NASA Astrophysics Data System (ADS)

Pai, Tun-Wen; Shyu, Keh-Hwa; Chen, Ling-Fan; Tai, Gwo-Chin

1995-04-01

This paper proposes an efficient technique of shape feature extraction based on the application of mathematical morphology theory. A new shape complexity index for preclassification of machine printed Chinese Character Recognition (CCR) is also proposed. For characters represented in different fonts/sizes or in a low resolution environment, a more stable local feature such as shape structure is preferred for character recognition. Morphological valley extraction filters are applied to extract the protrusive strokes from four sides of an input Chinese character. The number of extracted local strokes reflects the shape complexity of each side. These shape features of characters are encoded as corresponding shape complexity indices. Based on the shape complexity index, data base is able to be classified into 16 groups prior to recognition procedures. The performance of associating with shape feature analysis reclaims several characters from misrecognized character sets and results in an average of 3.3% improvement of recognition rate from an existing recognition system. In addition to enhance the recognition performance, the extracted stroke information can be further analyzed and classified its own stroke type. Therefore, the combination of extracted strokes from each side provides a means for data base clustering based on radical or subword components. It is one of the best solutions for recognizing high complexity characters such as Chinese characters which are divided into more than 200 different categories and consist more than 13,000 characters.

Shape recognition contributions to figure-ground reversal: which route counts?

PubMed

Peterson, M A; Harvey, E M; Weidenbacher, H J

1991-11-01

Observers viewed upright and inverted versions of figure-ground stimuli, in which Gestalt variables specified that the center was figure. In upright versions, the surround was high in denotivity, in that most viewers agreed it depicted the same shape; in inverted versions, the surround was low in denotivity. The surround was maintained as figure longer and was more likely to be obtained as figure when the stimuli were upright rather than inverted. In four experiments, these effects reflected inputs to figure-ground computations from orientation-specific shape representations only. To account for these findings, a nonratiomorphic mechanism is proposed that enables shape recognition processes before figure-ground relationships are determined.

Human detection in sensitive security areas through recognition of omega shapes using MACH filters

NASA Astrophysics Data System (ADS)

Rehman, Saad; Riaz, Farhan; Hassan, Ali; Liaquat, Muwahida; Young, Rupert

2015-03-01

Human detection has gained considerable importance in aggravated security scenarios over recent times. An effective security application relies strongly on detailed information regarding the scene under consideration. A larger accumulation of humans than the number of personal authorized to visit a security controlled area must be effectively detected, amicably alarmed and immediately monitored. A framework involving a novel combination of some existing techniques allows an immediate detection of an undesirable crowd in a region under observation. Frame differencing provides a clear visibility of moving objects while highlighting those objects in each frame acquired by a real time camera. Training of a correlation pattern recognition based filter on desired shapes such as elliptical representations of human faces (variants of an Omega Shape) yields correct detections. The inherent ability of correlation pattern recognition filters caters for angular rotations in the target object and renders decision regarding the existence of the number of persons exceeding an allowed figure in the monitored area.

The effect of colour congruency on shape discriminations of novel objects.

PubMed

Nicholson, Karen G; Humphrey, G Keith

2004-01-01

Although visual object recognition is primarily shape driven, colour assists the recognition of some objects. It is unclear, however, just how colour information is coded with respect to shape in long-term memory and how the availability of colour in the visual image facilitates object recognition. We examined the role of colour in the recognition of novel, 3-D objects by manipulating the congruency of object colour across the study and test phases, using an old/new shape-identification task. In experiment 1, we found that participants were faster at correctly identifying old objects on the basis of shape information when these objects were presented in their original colour, rather than in a different colour. In experiments 2 and 3, we found that participants were faster at correctly identifying old objects on the basis of shape information when these objects were presented with their original part-colour conjunctions, rather than in different or in reversed part-colour conjunctions. In experiment 4, we found that participants were quite poor at the verbal recall of part-colour conjunctions for correctly identified old objects, presented as grey-scale images at test. In experiment 5, we found that participants were significantly slower at correctly identifying old objects when object colour was incongruent across study and test, than when background colour was incongruent across study and test. The results of these experiments suggest that both shape and colour information are stored as part of the long-term representation of these novel objects. Results are discussed in terms of how colour might be coded with respect to shape in stored object representations.

Language comprehenders retain implied shape and orientation of objects.

PubMed

Pecher, Diane; van Dantzig, Saskia; Zwaan, Rolf A; Zeelenberg, René

2009-06-01

According to theories of embodied cognition, language comprehenders simulate sensorimotor experiences to represent the meaning of what they read. Previous studies have shown that picture recognition is better if the object in the picture matches the orientation or shape implied by a preceding sentence. In order to test whether strategic imagery may explain previous findings, language comprehenders first read a list of sentences in which objects were mentioned. Only once the complete list had been read was recognition memory tested with pictures. Recognition performance was better if the orientation or shape of the object matched that implied by the sentence, both immediately after reading the complete list of sentences and after a 45-min delay. These results suggest that previously found match effects were not due to strategic imagery and show that details of sensorimotor simulations are retained over longer periods.

Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

PubMed Central

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-01-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

Shape adaptive, robust iris feature extraction from noisy iris images.

PubMed

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-10-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

Comparing object recognition from binary and bipolar edge images for visual prostheses

PubMed Central

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2017-01-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition. PMID:28458481

Shape Recognition Inputs to Figure-Ground Organization in Three-Dimensional Displays.

ERIC Educational Resources Information Center

Peterson, Mary A.; Gibson, Bradley S.

1993-01-01

Three experiments with 29 college students and 8 members of a university community demonstrate that shape recognition processes influence perceived figure-ground relationships in 3-dimensional displays when the edge between 2 potential figural regions is both a luminance contrast edge and a disparity edge. Implications for shape recognition and…

Effects of Iris Surface Curvature on Iris Recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Joseph T; Flynn, Patrick J; Bowyer, Kevin W

To focus on objects at various distances, the lens of the eye must change shape to adjust its refractive power. This change in lens shape causes a change in the shape of the iris surface which can be measured by examining the curvature of the iris. This work isolates the variable of iris curvature in the recognition process and shows that differences in iris curvature degrade matching ability. To our knowledge, no other work has examined the effects of varying iris curvature on matching ability. To examine this degradation, we conduct a matching experiment across pairs of images with varyingmore » degrees of iris curvature differences. The results show a statistically signi cant degradation in matching ability. Finally, the real world impact of these ndings is discussed« less

Changes in Visual Object Recognition Precede the Shape Bias in Early Noun Learning

PubMed Central

Yee, Meagan; Jones, Susan S.; Smith, Linda B.

2012-01-01

Two of the most formidable skills that characterize human beings are language and our prowess in visual object recognition. They may also be developmentally intertwined. Two experiments, a large sample cross-sectional study and a smaller sample 6-month longitudinal study of 18- to 24-month-olds, tested a hypothesized developmental link between changes in visual object representation and noun learning. Previous findings in visual object recognition indicate that children’s ability to recognize common basic level categories from sparse structural shape representations of object shape emerges between the ages of 18 and 24 months, is related to noun vocabulary size, and is lacking in children with language delay. Other research shows in artificial noun learning tasks that during this same developmental period, young children systematically generalize object names by shape, that this shape bias predicts future noun learning, and is lacking in children with language delay. The two experiments examine the developmental relation between visual object recognition and the shape bias for the first time. The results show that developmental changes in visual object recognition systematically precede the emergence of the shape bias. The results suggest a developmental pathway in which early changes in visual object recognition that are themselves linked to category learning enable the discovery of higher-order regularities in category structure and thus the shape bias in novel noun learning tasks. The proposed developmental pathway has implications for understanding the role of specific experience in the development of both visual object recognition and the shape bias in early noun learning. PMID:23227015

Support vector machine-based facial-expression recognition method combining shape and appearance

NASA Astrophysics Data System (ADS)

Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

2010-11-01

Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

3D automatic anatomy recognition based on iterative graph-cut-ASM

NASA Astrophysics Data System (ADS)

Chen, Xinjian; Udupa, Jayaram K.; Bagci, Ulas; Alavi, Abass; Torigian, Drew A.

2010-02-01

We call the computerized assistive process of recognizing, delineating, and quantifying organs and tissue regions in medical imaging, occurring automatically during clinical image interpretation, automatic anatomy recognition (AAR). The AAR system we are developing includes five main parts: model building, object recognition, object delineation, pathology detection, and organ system quantification. In this paper, we focus on the delineation part. For the modeling part, we employ the active shape model (ASM) strategy. For recognition and delineation, we integrate several hybrid strategies of combining purely image based methods with ASM. In this paper, an iterative Graph-Cut ASM (IGCASM) method is proposed for object delineation. An algorithm called GC-ASM was presented at this symposium last year for object delineation in 2D images which attempted to combine synergistically ASM and GC. Here, we extend this method to 3D medical image delineation. The IGCASM method effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. We propose a new GC cost function, which effectively integrates the specific image information with the ASM shape model information. The proposed methods are tested on a clinical abdominal CT data set. The preliminary results show that: (a) it is feasible to explicitly bring prior 3D statistical shape information into the GC framework; (b) the 3D IGCASM delineation method improves on ASM and GC and can provide practical operational time on clinical images.

Contour matching for a fish recognition and migration-monitoring system

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Schoenberger, Robert B.; Shiozawa, Dennis; Xu, Xiaoqian; Zhan, Pengcheng

2004-12-01

Fish migration is being monitored year round to provide valuable information for the study of behavioral responses of fish to environmental variations. However, currently all monitoring is done by human observers. An automatic fish recognition and migration monitoring system is more efficient and can provide more accurate data. Such a system includes automatic fish image acquisition, contour extraction, fish categorization, and data storage. Shape is a very important characteristic and shape analysis and shape matching are studied for fish recognition. Previous work focused on finding critical landmark points on fish shape using curvature function analysis. Fish recognition based on landmark points has shown satisfying results. However, the main difficulty of this approach is that landmark points sometimes cannot be located very accurately. Whole shape matching is used for fish recognition in this paper. Several shape descriptors, such as Fourier descriptors, polygon approximation and line segments, are tested. A power cepstrum technique has been developed in order to improve the categorization speed using contours represented in tangent space with normalized length. Design and integration including image acquisition, contour extraction and fish categorization are discussed in this paper. Fish categorization results based on shape analysis and shape matching are also included.

Method and System for Object Recognition Search

NASA Technical Reports Server (NTRS)

Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

2012-01-01

A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

Feature binding and attention in working memory: a resolution of previous contradictory findings.

PubMed

Allen, Richard J; Hitch, Graham J; Mate, Judit; Baddeley, Alan D

2012-01-01

We aimed to resolve an apparent contradiction between previous experiments from different laboratories, using dual-task methodology to compare effects of a concurrent executive load on immediate recognition memory for colours or shapes of items or their colour-shape combinations. Results of two experiments confirmed previous evidence that an irrelevant attentional load interferes equally with memory for features and memory for feature bindings. Detailed analyses suggested that previous contradictory evidence arose from limitations in the way recognition memory was measured. The present findings are inconsistent with an earlier suggestion that feature binding takes place within a multimodal episodic buffer Baddeley, ( 2000 ) and support a subsequent account in which binding takes place automatically prior to information entering the episodic buffer Baddeley, Allen, & Hitch, ( 2011 ). Methodologically, the results suggest that different measures of recognition memory performance (A', d', corrected recognition) give a converging picture of main effects, but are less consistent in detecting interactions. We suggest that this limitation on the reliability of measuring recognition should be taken into account in future research so as to avoid problems of replication that turn out to be more apparent than real.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Recognition ROCS Are Curvilinear--Or Are They? On Premature Arguments against the Two-High-Threshold Model of Recognition

ERIC Educational Resources Information Center

Broder, Arndt; Schutz, Julia

2009-01-01

Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to…

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

The interplay of holistic shape, local feature and color information in object categorization.

PubMed

Rokszin, Adrienn Aranka; Győri-Dani, Dóra; Linnert, Szilvia; Krajcsi, Attila; Tompa, Tamás; Csifcsák, Gábor

2015-07-01

Although it is widely accepted that colors facilitate object and scene recognition under various circumstances, several studies found no effects of color removal in tasks requiring categorization of briefly presented animals in natural scenes. In this study, three experiments were performed to test the assumption that the discrepancy between empirical data is related to variations of the available meaningful global information such as object shapes and contextual cues. Sixty-one individuals categorized chromatic and achromatic versions of intact and scrambled images containing either cars or birds. While color removal did not affect the classification of intact stimuli, the recognition of moderately scrambled achromatic images was more difficult. This effect was accompanied by amplitude modulations of occipital event-related potentials emerging from approximately 150ms post-stimulus. Our results indicate that colors facilitate stimulus classification, but this effect becomes prominent only in cases when holistic processing is not sufficient for stimulus recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Qualitative Differences in the Representation of Spatial Relations for Different Object Classes

ERIC Educational Resources Information Center

Cooper, Eric E.; Brooks, Brian E.

2004-01-01

Two experiments investigated whether the representations used for animal, produce, and object recognition code spatial relations in a similar manner. Experiment 1 tested the effects of planar rotation on the recognition of animals and nonanimal objects. Response times for recognizing animals followed an inverted U-shaped function, whereas those…

Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

NASA Astrophysics Data System (ADS)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.

Contributions of feature shapes and surface cues to the recognition and neural representation of facial identity.

PubMed

Andrews, Timothy J; Baseler, Heidi; Jenkins, Rob; Burton, A Mike; Young, Andrew W

2016-10-01

A full understanding of face recognition will involve identifying the visual information that is used to discriminate different identities and how this is represented in the brain. The aim of this study was to explore the importance of shape and surface properties in the recognition and neural representation of familiar faces. We used image morphing techniques to generate hybrid faces that mixed shape properties (more specifically, second order spatial configural information as defined by feature positions in the 2D-image) from one identity and surface properties from a different identity. Behavioural responses showed that recognition and matching of these hybrid faces was primarily based on their surface properties. These behavioural findings contrasted with neural responses recorded using a block design fMRI adaptation paradigm to test the sensitivity of Haxby et al.'s (2000) core face-selective regions in the human brain to the shape or surface properties of the face. The fusiform face area (FFA) and occipital face area (OFA) showed a lower response (adaptation) to repeated images of the same face (same shape, same surface) compared to different faces (different shapes, different surfaces). From the behavioural data indicating the critical contribution of surface properties to the recognition of identity, we predicted that brain regions responsible for familiar face recognition should continue to adapt to faces that vary in shape but not surface properties, but show a release from adaptation to faces that vary in surface properties but not shape. However, we found that the FFA and OFA showed an equivalent release from adaptation to changes in both shape and surface properties. The dissociation between the neural and perceptual responses suggests that, although they may play a role in the process, these core face regions are not solely responsible for the recognition of facial identity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recognition intent and visual word recognition.

PubMed

Wang, Man-Ying; Ching, Chi-Le

2009-03-01

This study adopted a change detection task to investigate whether and how recognition intent affects the construction of orthographic representation in visual word recognition. Chinese readers (Experiment 1-1) and nonreaders (Experiment 1-2) detected color changes in radical components of Chinese characters. Explicit recognition demand was imposed in Experiment 2 by an additional recognition task. When the recognition was implicit, a bias favoring the radical location informative of character identity was found in Chinese readers (Experiment 1-1), but not nonreaders (Experiment 1-2). With explicit recognition demands, the effect of radical location interacted with radical function and word frequency (Experiment 2). An estimate of identification performance under implicit recognition was derived in Experiment 3. These findings reflect the joint influence of recognition intent and orthographic regularity in shaping readers' orthographic representation. The implication for the role of visual attention in word recognition was also discussed.

Neural correlates of facilitations in face learning by selective caricaturing of facial shape or reflectance.

PubMed

Itz, Marlena L; Schweinberger, Stefan R; Schulz, Claudia; Kaufmann, Jürgen M

2014-11-15

Spatially caricatured faces were recently shown to benefit face learning (Schulz et al., 2012a). Moreover, spatial information may be particularly important for encoding unfamiliar faces, but less so for recognizing familiar faces (Kaufmann et al., 2013). To directly test the possibility of a major role of reflectance information for the recognition of familiar faces, we compared effects of selective photorealistic caricaturing in either shape or reflectance on face learning and recognition. Participants learned 3D-photographed faces across different viewpoints, and different images were presented at learning and test. At test, performance benefits for both types of caricatures were modulated by familiarity: Benefits for learned faces were substantially larger for reflectance caricatures, whereas benefits for novel faces were numerically larger for shape caricatures. ERPs confirmed a consistent reduction of the occipitotemporal P200 (200-240 ms) by shape caricaturing, whereas the most prominent effect of reflectance caricaturing was seen in an enhanced posterior N250 (240-400 ms), a component that has been related to the activation of acquired face representations. Our results suggest that performance benefits for face learning caused by distinctive spatial versus reflectance information are mediated by different neural processes with different timing and support a prominent role of reflectance for the recognition of learned faces. Copyright © 2014 Elsevier Inc. All rights reserved.

Contributions of feature shapes and surface cues to the recognition of facial expressions.

PubMed

Sormaz, Mladen; Young, Andrew W; Andrews, Timothy J

2016-10-01

Theoretical accounts of face processing often emphasise feature shapes as the primary visual cue to the recognition of facial expressions. However, changes in facial expression also affect the surface properties of the face. In this study, we investigated whether this surface information can also be used in the recognition of facial expression. First, participants identified facial expressions (fear, anger, disgust, sadness, happiness) from images that were manipulated such that they varied mainly in shape or mainly in surface properties. We found that the categorization of facial expression is possible in either type of image, but that different expressions are relatively dependent on surface or shape properties. Next, we investigated the relative contributions of shape and surface information to the categorization of facial expressions. This employed a complementary method that involved combining the surface properties of one expression with the shape properties from a different expression. Our results showed that the categorization of facial expressions in these hybrid images was equally dependent on the surface and shape properties of the image. Together, these findings provide a direct demonstration that both feature shape and surface information make significant contributions to the recognition of facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Preserved Haptic Shape Processing after Bilateral LOC Lesions.

PubMed

Snow, Jacqueline C; Goodale, Melvyn A; Culham, Jody C

2015-10-07

The visual and haptic perceptual systems are understood to share a common neural representation of object shape. A region thought to be critical for recognizing visual and haptic shape information is the lateral occipital complex (LOC). We investigated whether LOC is essential for haptic shape recognition in humans by studying behavioral responses and brain activation for haptically explored objects in a patient (M.C.) with bilateral lesions of the occipitotemporal cortex, including LOC. Despite severe deficits in recognizing objects using vision, M.C. was able to accurately recognize objects via touch. M.C.'s psychophysical response profile to haptically explored shapes was also indistinguishable from controls. Using fMRI, M.C. showed no object-selective visual or haptic responses in LOC, but her pattern of haptic activation in other brain regions was remarkably similar to healthy controls. Although LOC is routinely active during visual and haptic shape recognition tasks, it is not essential for haptic recognition of object shape. The lateral occipital complex (LOC) is a brain region regarded to be critical for recognizing object shape, both in vision and in touch. However, causal evidence linking LOC with haptic shape processing is lacking. We studied recognition performance, psychophysical sensitivity, and brain response to touched objects, in a patient (M.C.) with extensive lesions involving LOC bilaterally. Despite being severely impaired in visual shape recognition, M.C. was able to identify objects via touch and she showed normal sensitivity to a haptic shape illusion. M.C.'s brain response to touched objects in areas of undamaged cortex was also very similar to that observed in neurologically healthy controls. These results demonstrate that LOC is not necessary for recognizing objects via touch. Copyright © 2015 the authors 0270-6474/15/3513745-16$15.00/0.

Parts and Relations in Young Children's Shape-Based Object Recognition

ERIC Educational Resources Information Center

Augustine, Elaine; Smith, Linda B.; Jones, Susan S.

2011-01-01

The ability to recognize common objects from sparse information about geometric shape emerges during the same period in which children learn object names and object categories. Hummel and Biederman's (1992) theory of object recognition proposes that the geometric shapes of objects have two components--geometric volumes representing major object…

Online Farsi digit recognition using their upper half structure

NASA Astrophysics Data System (ADS)

Ghods, Vahid; Sohrabi, Mohammad Karim

2015-03-01

In this paper, we investigated the efficiency of upper half Farsi numerical digit structure. In other words, half of data (upper half of the digit shapes) was exploited for the recognition of Farsi numerical digits. This method can be used for both offline and online recognition. Half of data is more effective in speed process, data transfer and in this application accuracy. Hidden Markov model (HMM) was used to classify online Farsi digits. Evaluation was performed by TMU dataset. This dataset contains more than 1200 samples of online handwritten Farsi digits. The proposed method yielded more accuracy in recognition rate.

Circular blurred shape model for multiclass symbol recognition.

PubMed

Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia

2011-04-01

In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.

Personal recognition using hand shape and texture.

PubMed

Kumar, Ajay; Zhang, David

2006-08-01

This paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), k-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems.

Event-related potentials during word mapping to object shape predict toddlers' vocabulary size

PubMed Central

Borgström, Kristina; Torkildsen, Janne von Koss; Lindgren, Magnus

2015-01-01

What role does attention to different object properties play in early vocabulary development? This longitudinal study using event-related potentials in combination with behavioral measures investigated 20- and 24-month-olds' (n = 38; n = 34; overlapping n = 24) ability to use object shape and object part information in word-object mapping. The N400 component was used to measure semantic priming by images containing shape or detail information. At 20 months, the N400 to words primed by object shape varied in topography and amplitude depending on vocabulary size, and these differences predicted productive vocabulary size at 24 months. At 24 months, when most of the children had vocabularies of several hundred words, the relation between vocabulary size and the N400 effect in a shape context was weaker. Detached object parts did not function as word primes regardless of age or vocabulary size, although the part-objects were identified behaviorally. The behavioral measure, however, also showed relatively poor recognition of the part-objects compared to the shape-objects. These three findings provide new support for the link between shape recognition and early vocabulary development. PMID:25762957

Basic perceptual changes that alter meaning and neural correlates of recognition memory

PubMed Central

Gao, Chuanji; Hermiller, Molly S.; Voss, Joel L.; Guo, Chunyan

2015-01-01

It is difficult to pinpoint the border between perceptual and conceptual processing, despite their treatment as distinct entities in many studies of recognition memory. For instance, alteration of simple perceptual characteristics of a stimulus can radically change meaning, such as the color of bread changing from white to green. We sought to better understand the role of perceptual and conceptual processing in memory by identifying the effects of changing a basic perceptual feature (color) on behavioral and neural correlates of memory in circumstances when this change would be expected to either change the meaning of a stimulus or to have no effect on meaning (i.e., to influence conceptual processing or not). Abstract visual shapes (“squiggles”) were colorized during study and presented during test in either the same color or a different color. Those squiggles that subjects found to resemble meaningful objects supported behavioral measures of conceptual priming, whereas meaningless squiggles did not. Further, changing color from study to test had a selective effect on behavioral correlates of priming for meaningful squiggles, indicating that color change altered conceptual processing. During a recognition memory test, color change altered event-related brain potential (ERP) correlates of memory for meaningful squiggles but not for meaningless squiggles. Specifically, color change reduced the amplitude of frontally distributed N400 potentials (FN400), implying that these potentials indicated conceptual processing during recognition memory that was sensitive to color change. In contrast, color change had no effect on FN400 correlates of recognition for meaningless squiggles, which were overall smaller in amplitude than for meaningful squiggles (further indicating that these potentials signal conceptual processing during recognition). Thus, merely changing the color of abstract visual shapes can alter their meaning, changing behavioral and neural correlates of memory. These findings are relevant to understanding similarities and distinctions between perceptual and conceptual processing as well as the functional interpretation of neural correlates of recognition memory. PMID:25717298

Variations in Recollection: The Effects of Complexity on Source Recognition

ERIC Educational Resources Information Center

Parks, Colleen M.; Murray, Linda J.; Elfman, Kane; Yonelinas, Andrew P.

2011-01-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in…

Hierarchical human action recognition around sleeping using obscured posture information

NASA Astrophysics Data System (ADS)

Kudo, Yuta; Sashida, Takehiko; Aoki, Yoshimitsu

2015-04-01

This paper presents a new approach for human action recognition around sleeping with the human body parts locations and the positional relationship between human and sleeping environment. Body parts are estimated from the depth image obtained by a time-of-flight (TOF) sensor using oriented 3D normal vector. Issues in action recognition of sleeping situation are the demand of availability in darkness, and hiding of the human body by duvets. Therefore, the extraction of image features is difficult since color and edge features are obscured by covers. Thus, first in our method, positions of four parts of the body (head, torso, thigh, and lower leg) are estimated by using the shape model of bodily surface constructed by oriented 3D normal vector. This shape model can represent the surface shape of rough body, and is effective in robust posture estimation of the body hidden with duvets. Then, action descriptor is extracted from the position of each body part. The descriptor includes temporal variation of each part of the body and spatial vector of position of the parts and the bed. Furthermore, this paper proposes hierarchical action classes and classifiers to improve the indistinct action classification. Classifiers are composed of two layers, and recognize human action by using the action descriptor. First layer focuses on spatial descriptor and classifies action roughly. Second layer focuses on temporal descriptor and classifies action finely. This approach achieves a robust recognition of obscured human by using the posture information and the hierarchical action recognition.

Caricature generalization benefits for faces learned with enhanced idiosyncratic shape or texture.

PubMed

Itz, Marlena L; Schweinberger, Stefan R; Kaufmann, Jürgen M

2017-02-01

Recent findings show benefits for learning and subsequent recognition of faces caricatured in shape or texture, but there is little evidence on whether this caricature learning advantage generalizes to recognition of veridical counterparts at test. Moreover, it has been reported that there is a relatively higher contribution of texture information, at the expense of shape information, for familiar compared to unfamiliar face recognition. The aim of this study was to examine whether veridical faces are recognized better when they were learned as caricatures compared to when they were learned as veridicals-what we call a caricature generalization benefit. Photorealistic facial stimuli derived from a 3-D camera system were caricatured selectively in either shape or texture by 50 %. Faces were learned across different images either as veridicals, shape caricatures, or texture caricatures. At test, all learned and novel faces were presented as previously unseen frontal veridicals, and participants performed an old-new task. We assessed accuracies, reaction times, and face-sensitive event-related potentials (ERPs). Faces learned as caricatures were recognized more accurately than faces learned as veridicals. At learning, N250 and LPC were largest for shape caricatures, suggesting encoding advantages of distinctive facial shape. At test, LPC was largest for faces that had been learned as texture caricatures, indicating the importance of texture for familiar face recognition. Overall, our findings demonstrate that caricature learning advantages can generalize to and, importantly, improve recognition of veridical versions of faces.

Object/Shape Recognition Technology: An Assessment of the Feasibility of Implementation at Defense Logistics Agency Disposition Services

DTIC Science & Technology

2015-02-25

provide efficiency and effectively manufacture or inventory items. The industries that benefit from Cognex technology are automotive, food and beverage ...recognition tedmology, Tedmology Readiness Level, PAGES Cost Benefit Analysis, Tedmology Commercialization, Technology Transition 139 16. PRICE CODE 17...Technology Development & Transition Strategy Guidebook xvii UD Ultimate Disposal U.S. United States USAF United States Air Force xviii THIS

The influence of averaging and noisy decision strategies on the recognition memory ROC.

PubMed

Malmberg, Kenneth J; Xu, Jing

2006-02-01

Many single- and dual-process models of recognition memory predict that the ratings and remember-know receiver operating characteristics (ROCs) are the same, but Rotello, Macmillan, and Reeder (2004) reported that the slopes of the remember-know and ratings z-transformed ROCs (zROCs) are different The authors show that averaging introduces nonlinearities to the form of the zROC and that ratings and remember-know zROCs are indistinguishable when constructed in a conventional manner. The authors show, further, that some nonoptimal decision strategies have a distinctive, nonlinear effect on the form of the single-process continuous-state zROC. The conclusion is that many factors having nothing to do with the nature of recognition memory can affect the shape of zROCs, and that therefore, the shape of the zROC does not, alone, characterize different memory models.

Short temporal asynchrony disrupts visual object recognition

PubMed Central

Singer, Jedediah M.; Kreiman, Gabriel

2014-01-01

Humans can recognize objects and scenes in a small fraction of a second. The cascade of signals underlying rapid recognition might be disrupted by temporally jittering different parts of complex objects. Here we investigated the time course over which shape information can be integrated to allow for recognition of complex objects. We presented fragments of object images in an asynchronous fashion and behaviorally evaluated categorization performance. We observed that visual recognition was significantly disrupted by asynchronies of approximately 30 ms, suggesting that spatiotemporal integration begins to break down with even small deviations from simultaneity. However, moderate temporal asynchrony did not completely obliterate recognition; in fact, integration of visual shape information persisted even with an asynchrony of 100 ms. We describe the data with a concise model based on the dynamic reduction of uncertainty about what image was presented. These results emphasize the importance of timing in visual processing and provide strong constraints for the development of dynamical models of visual shape recognition. PMID:24819738

Orientation congruency effects for familiar objects: coordinate transformations in object recognition.

PubMed

Graf, M; Kaping, D; Bülthoff, H H

2005-03-01

How do observers recognize objects after spatial transformations? Recent neurocomputational models have proposed that object recognition is based on coordinate transformations that align memory and stimulus representations. If the recognition of a misoriented object is achieved by adjusting a coordinate system (or reference frame), then recognition should be facilitated when the object is preceded by a different object in the same orientation. In the two experiments reported here, two objects were presented in brief masked displays that were in close temporal contiguity; the objects were in either congruent or incongruent picture-plane orientations. Results showed that naming accuracy was higher for congruent than for incongruent orientations. The congruency effect was independent of superordinate category membership (Experiment 1) and was found for objects with different main axes of elongation (Experiment 2). The results indicate congruency effects for common familiar objects even when they have dissimilar shapes. These findings are compatible with models in which object recognition is achieved by an adjustment of a perceptual coordinate system.

Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

PubMed Central

Azzopardi, George; Petkov, Nicolai

2014-01-01

The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 → V4 → TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. An S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms. PMID:25126068

The Potato Chip Really Does Look Like Elvis! Neural Hallmarks of Conceptual Processing Associated with Finding Novel Shapes Subjectively Meaningful

PubMed Central

Federmeier, Kara D.; Paller, Ken A.

2012-01-01

Clouds and inkblots often compellingly resemble something else—faces, animals, or other identifiable objects. Here, we investigated illusions of meaning produced by novel visual shapes. Individuals found some shapes meaningful and others meaningless, with considerable variability among individuals in these subjective categorizations. Repetition for shapes endorsed as meaningful produced conceptual priming in a priming test along with concurrent activity reductions in cortical regions associated with conceptual processing of real objects. Subjectively meaningless shapes elicited robust activity in the same brain areas, but activity was not influenced by repetition. Thus, all shapes were conceptually evaluated, but stable conceptual representations supported neural priming for meaningful shapes only. During a recognition memory test, performance was associated with increased frontoparietal activity, regardless of meaningfulness. In contrast, neural conceptual priming effects for meaningful shapes occurred during both priming and recognition testing. These different patterns of brain activation as a function of stimulus repetition, type of memory test, and subjective meaningfulness underscore the distinctive neural bases of conceptual fluency versus episodic memory retrieval. Finding meaning in ambiguous stimuli appears to depend on conceptual evaluation and cortical processing events similar to those typically observed for known objects. To the brain, the vaguely Elvis-like potato chip truly can provide a substitute for the King himself. PMID:22079921

3D face analysis by using Mesh-LBP feature

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

Objective: Face Recognition is one of the widely application of image processing. Corresponding two-dimensional limitations, such as the pose and illumination changes, to a certain extent restricted its accurate rate and further development. How to overcome the pose and illumination changes and the effects of self-occlusion is the research hotspot and difficulty, also attracting more and more domestic and foreign experts and scholars to study it. 3D face recognition fusing shape and texture descriptors has become a very promising research direction. Method: Our paper presents a 3D point cloud based on mesh local binary pattern grid (Mesh-LBP), then feature extraction for 3D face recognition by fusing shape and texture descriptors. 3D Mesh-LBP not only retains the integrity of the 3D geometry, is also reduces the need for recognition process of normalization steps, because the triangle Mesh-LBP descriptor is calculated on 3D grid. On the other hand, in view of multi-modal consistency in face recognition advantage, construction of LBP can fusing shape and texture information on Triangular Mesh. In this paper, some of the operators used to extract Mesh-LBP, Such as the normal vectors of the triangle each face and vertex, the gaussian curvature, the mean curvature, laplace operator and so on. Conclusion: First, Kinect devices obtain 3D point cloud face, after the pretreatment and normalization, then transform it into triangular grid, grid local binary pattern feature extraction from face key significant parts of face. For each local face, calculate its Mesh-LBP feature with Gaussian curvature, mean curvature laplace operator and so on. Experiments on the our research database, change the method is robust and high recognition accuracy.

Does viotin activate violin more than viocin? On the use of visual cues during visual-word recognition.

PubMed

Perea, Manuel; Panadero, Victoria

2014-01-01

The vast majority of neural and computational models of visual-word recognition assume that lexical access is achieved via the activation of abstract letter identities. Thus, a word's overall shape should play no role in this process. In the present lexical decision experiment, we compared word-like pseudowords like viotín (same shape as its base word: violín) vs. viocín (different shape) in mature (college-aged skilled readers), immature (normally reading children), and immature/impaired (young readers with developmental dyslexia) word-recognition systems. Results revealed similar response times (and error rates) to consistent-shape and inconsistent-shape pseudowords for both adult skilled readers and normally reading children - this is consistent with current models of visual-word recognition. In contrast, young readers with developmental dyslexia made significantly more errors to viotín-like pseudowords than to viocín-like pseudowords. Thus, unlike normally reading children, young readers with developmental dyslexia are sensitive to a word's visual cues, presumably because of poor letter representations.

Color constancy in 3D-2D face recognition

NASA Astrophysics Data System (ADS)

Meyer, Manuel; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis A.

2013-05-01

Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.

Automated transformation-invariant shape recognition through wavelet multiresolution

NASA Astrophysics Data System (ADS)

Brault, Patrice; Mounier, Hugues

2001-12-01

We present here new results in Wavelet Multi-Resolution Analysis (W-MRA) applied to shape recognition in automatic vehicle driving applications. Different types of shapes have to be recognized in this framework. They pertain to most of the objects entering the sensors field of a car. These objects can be road signs, lane separation lines, moving or static obstacles, other automotive vehicles, or visual beacons. The recognition process must be invariant to global, affine or not, transformations which are : rotation, translation and scaling. It also has to be invariant to more local, elastic, deformations like the perspective (in particular with wide angle camera lenses), and also like deformations due to environmental conditions (weather : rain, mist, light reverberation) or optical and electrical signal noises. To demonstrate our method, an initial shape, with a known contour, is compared to the same contour altered by rotation, translation, scaling and perspective. The curvature computed for each contour point is used as a main criterion in the shape matching process. The original part of this work is to use wavelet descriptors, generated with a fast orthonormal W-MRA, rather than Fourier descriptors, in order to provide a multi-resolution description of the contour to be analyzed. In such way, the intrinsic spatial localization property of wavelet descriptors can be used and the recognition process can be speeded up. The most important part of this work is to demonstrate the potential performance of Wavelet-MRA in this application of shape recognition.

A Biological-Plausable Architecture for Shape Recognition

DTIC Science & Technology

2006-06-30

between curves. Information Processing Letters, 64, 1997. [4] Irving Biederman . Recognition-by-components: A theory of human image understanding...Psychological Review, 94(2):115–147, 1987 . 43 [5] C. Cadieu, M. Kouh, M. Riesenhuber, and T. Poggio. Shape representation in v4: Investi- gating position

Three-dimensional deformable-model-based localization and recognition of road vehicles.

PubMed

Zhang, Zhaoxiang; Tan, Tieniu; Huang, Kaiqi; Wang, Yunhong

2012-01-01

We address the problem of model-based object recognition. Our aim is to localize and recognize road vehicles from monocular images or videos in calibrated traffic scenes. A 3-D deformable vehicle model with 12 shape parameters is set up as prior information, and its pose is determined by three parameters, which are its position on the ground plane and its orientation about the vertical axis under ground-plane constraints. An efficient local gradient-based method is proposed to evaluate the fitness between the projection of the vehicle model and image data, which is combined into a novel evolutionary computing framework to estimate the 12 shape parameters and three pose parameters by iterative evolution. The recovery of pose parameters achieves vehicle localization, whereas the shape parameters are used for vehicle recognition. Numerous experiments are conducted in this paper to demonstrate the performance of our approach. It is shown that the local gradient-based method can evaluate accurately and efficiently the fitness between the projection of the vehicle model and the image data. The evolutionary computing framework is effective for vehicles of different types and poses is robust to all kinds of occlusion.

Branch length similarity entropy-based descriptors for shape representation

NASA Astrophysics Data System (ADS)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.

The cultural life script as cognitive schema: how the life script shapes memory for fictional life stories.

PubMed

Koppel, Jonathan; Berntsen, Dorthe

2014-01-01

We tested, across three studies, the effect of the cultural life script on memory and its phenomenological properties. We focused in particular on the mnemonic effects of both schema-consistency and frequency in the life script. In addition to testing recognition (in Study 1) and recall (in Studies 2 and 3), we also collected remember/know judgements for remembered events (in Studies 1 and 2) and memory for their emotional valence (in Study 2). Our primary finding was that, across all three studies, higher-frequency events were more memorable than lower-frequency events, as measured through either recognition or recall. We also attained three additional, complementary effects: First, schema-inconsistent events received remember ratings more often than schema-consistent events (in Study 2, with a trend to this effect in Study 1); second, where an event's emotional valence was inconsistent with the life script, memory for its valence was reconstructed to fit the script (in Study 2); and, third, intrusions in recall were disproportionately for life script events (in Study 3), although that was not the case in recognition (in Study 1). We conclude that the life script serves as a cognitive schema in how it shapes memory and its phenomenological properties.

Configuration control on the shape memory stiffness of molecularly imprinted polymer for specific uptake of creatinine

NASA Astrophysics Data System (ADS)

Ang, Qian Yee; Zolkeflay, Muhammad Helmi; Low, Siew Chun

2016-04-01

In this study, sol-gel processing was proposed to prepare a creatinine (Cre)-imprinted molecularly imprinted polymer (MIP). The intermolecular interaction constituted by the cross-linkers, i.e., 2-acrylamido-2-methylpropane-sulfonic acid (AMPS) and aluminium ion (Al3+), was studied and compared in order to form a confined matrix that promises the effectiveness of molecular imprinting. In view of the shape recognition, the hydrogen bonded Cre-AMPS did not demonstrate good recognition of Cre, with Cre binding found only at 5.70 ± 0.15 mg g-1 of MIP. Whilst, MIP cross-linked using Al3+ was able to attain an excellent Cre adsorption capacity of 19.48 ± 0.64 mg g-1 of MIP via the stronger ionic interaction of Cre-Al3+. Based on the Scatchard analysis, a higher Cre concentration in testing solution required greater driving force to resolve the binding resistance of Cre molecules, so as to have a precise Cre binding with shape factor. The molecular recognition ability of Cre-MIP in present work was shape-specific for Cre as compared to its structural analogue, 2-pyrrolidinone (2-pyr), by an ideal selectivity coefficient of 6.57 ± 0.10. In overall, this study has come up with a practical approach on the preparation of MIP for the detection of renal dysfunction by point-of-care Cre testing.

Automatic casting surface defect recognition and classification

NASA Astrophysics Data System (ADS)

Wong, Boon K.; Elliot, M. P.; Rapley, C. W.

1995-03-01

High integrity castings require surfaces free from defects to reduce, if not eliminate, vulnerability to component failure from such as physical or thermal fatigue or corrosion attack. Previous studies have shown that defects on casting surfaces can be optically enhanced from the surrounding randomly textured surface by liquid penetrants, magnetic particle and other methods. However, very little has been reported on recognition and classification of the defects. The basic problem is one of shape recognition and classification, where the shape can vary in size and orientation as well as in actual shape generally within an envelope that classifies it as a particular defect. The initial work done towards this has focused on recognizing and classifying standard shapes such as the circle, square, rectangle and triangle. Various approaches were tried and this led eventually to a series of fuzzy logic based algorithms from which very good results were obtained. From this work fuzzy logic memberships were generated for the detection of defects found on casting surfaces. Simulated model shapes of such as the quench crack, mechanical crack and hole have been used to test the generated algorithm and the results for recognition and classification are very encouraging.

Face shape and face identity processing in behavioral variant fronto-temporal dementia: A specific deficit for familiarity and name recognition of famous faces.

PubMed

De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan

2016-01-01

Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.

Neural network application for thermal image recognition of low-resolution objects

NASA Astrophysics Data System (ADS)

Fang, Yi-Chin; Wu, Bo-Wen

2007-02-01

In the ever-changing situation on a battle field, accurate recognition of a distant object is critical to a commander's decision-making and the general public's safety. Efficiently distinguishing between an enemy's armoured vehicles and ordinary civilian houses under all weather conditions has become an important research topic. This study presents a system for recognizing an armoured vehicle by distinguishing marks and contours. The characteristics of 12 different shapes and 12 characters are used to explore thermal image recognition under the circumstance of long distance and low resolution. Although the recognition capability of human eyes is superior to that of artificial intelligence under normal conditions, it tends to deteriorate substantially under long-distance and low-resolution scenarios. This study presents an effective method for choosing features and processing images. The artificial neural network technique is applied to further improve the probability of accurate recognition well beyond the limit of the recognition capability of human eyes.

Short- and long-term effects of nicotine and the histone deacetylase inhibitor phenylbutyrate on novel object recognition in zebrafish.

PubMed

Faillace, M P; Pisera-Fuster, A; Medrano, M P; Bejarano, A C; Bernabeu, R O

2017-03-01

Zebrafish have a sophisticated color- and shape-sensitive visual system, so we examined color cue-based novel object recognition in zebrafish. We evaluated preference in the absence or presence of drugs that affect attention and memory retention in rodents: nicotine and the histone deacetylase inhibitor (HDACi) phenylbutyrate (PhB). The objective of this study was to evaluate whether nicotine and PhB affect innate preferences of zebrafish for familiar and novel objects after short- and long-retention intervals. We developed modified object recognition (OR) tasks using neutral novel and familiar objects in different colors. We also tested objects which differed with respect to the exploratory behavior they elicited from naïve zebrafish. Zebrafish showed an innate preference for exploring red or green objects rather than yellow or blue objects. Zebrafish were better at discriminating color changes than changes in object shape or size. Nicotine significantly enhanced or changed short-term innate novel object preference whereas PhB had similar effects when preference was assessed 24 h after training. Analysis of other zebrafish behaviors corroborated these results. Zebrafish were innately reluctant or prone to explore colored novel objects, so drug effects on innate preference for objects can be evaluated changing the color of objects with a simple geometry. Zebrafish exhibited recognition memory for novel objects with similar innate significance. Interestingly, nicotine and PhB significantly modified innate object preference.

Face recognition using 3D facial shape and color map information: comparison and combination

NASA Astrophysics Data System (ADS)

Godil, Afzal; Ressler, Sandy; Grother, Patrick

2004-08-01

In this paper, we investigate the use of 3D surface geometry for face recognition and compare it to one based on color map information. The 3D surface and color map data are from the CAESAR anthropometric database. We find that the recognition performance is not very different between 3D surface and color map information using a principal component analysis algorithm. We also discuss the different techniques for the combination of the 3D surface and color map information for multi-modal recognition by using different fusion approaches and show that there is significant improvement in results. The effectiveness of various techniques is compared and evaluated on a dataset with 200 subjects in two different positions.

Recognition of Similar Shaped Handwritten Marathi Characters Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Jane, Archana P.; Pund, Mukesh A.

2012-03-01

The growing need have handwritten Marathi character recognition in Indian offices such as passport, railways etc has made it vital area of a research. Similar shape characters are more prone to misclassification. In this paper a novel method is provided to recognize handwritten Marathi characters based on their features extraction and adaptive smoothing technique. Feature selections methods avoid unnecessary patterns in an image whereas adaptive smoothing technique form smooth shape of charecters.Combination of both these approaches leads to the better results. Previous study shows that, no one technique achieves 100% accuracy in handwritten character recognition area. This approach of combining both adaptive smoothing & feature extraction gives better results (approximately 75-100) and expected outcomes.

Clustering of Farsi sub-word images for whole-book recognition

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2015-01-01

Redundancy of word and sub-word occurrences in large documents can be effectively utilized in an OCR system to improve recognition results. Most OCR systems employ language modeling techniques as a post-processing step; however these techniques do not use important pictorial information that exist in the text image. In case of large-scale recognition of degraded documents, this information is even more valuable. In our previous work, we proposed a subword image clustering method for the applications dealing with large printed documents. In our clustering method, the ideal case is when all equivalent sub-word images lie in one cluster. To overcome the issues of low print quality, the clustering method uses an image matching algorithm for measuring the distance between two sub-word images. The measured distance with a set of simple shape features were used to cluster all sub-word images. In this paper, we analyze the effects of adding more shape features on processing time, purity of clustering, and the final recognition rate. Previously published experiments have shown the efficiency of our method on a book. Here we present extended experimental results and evaluate our method on another book with totally different font face. Also we show that the number of the new created clusters in a page can be used as a criteria for assessing the quality of print and evaluating preprocessing phases.

Multiscale characterization and analysis of shapes

DOEpatents

Prasad, Lakshman; Rao, Ramana

2002-01-01

An adaptive multiscale method approximates shapes with continuous or uniformly and densely sampled contours, with the purpose of sparsely and nonuniformly discretizing the boundaries of shapes at any prescribed resolution, while at the same time retaining the salient shape features at that resolution. In another aspect, a fundamental geometric filtering scheme using the Constrained Delaunay Triangulation (CDT) of polygonized shapes creates an efficient parsing of shapes into components that have semantic significance dependent only on the shapes' structure and not on their representations per se. A shape skeletonization process generalizes to sparsely discretized shapes, with the additional benefit of prunability to filter out irrelevant and morphologically insignificant features. The skeletal representation of characters of varying thickness and the elimination of insignificant and noisy spurs and branches from the skeleton greatly increases the robustness, reliability and recognition rates of character recognition algorithms.

Recognizing familiar objects by hand and foot: Haptic shape perception generalizes to inputs from unusual locations and untrained body parts.

PubMed

Lawson, Rebecca

2014-02-01

The limits of generalization of our 3-D shape recognition system to identifying objects by touch was investigated by testing exploration at unusual locations and using untrained effectors. In Experiments 1 and 2, people found identification by hand of real objects, plastic 3-D models of objects, and raised line drawings placed in front of themselves no easier than when exploration was behind their back. Experiment 3 compared one-handed, two-handed, one-footed, and two-footed haptic object recognition of familiar objects. Recognition by foot was slower (7 vs. 13 s) and much less accurate (9 % vs. 47 % errors) than recognition by either one or both hands. Nevertheless, item difficulty was similar across hand and foot exploration, and there was a strong correlation between an individual's hand and foot performance. Furthermore, foot recognition was better with the largest 20 of the 80 items (32 % errors), suggesting that physical limitations hampered exploration by foot. Thus, object recognition by hand generalized efficiently across the spatial location of stimuli, while object recognition by foot seemed surprisingly good given that no prior training was provided. Active touch (haptics) thus efficiently extracts 3-D shape information and accesses stored representations of familiar objects from novel modes of input.

Vibrotactile feedback for conveying object shape information as perceived by artificial sensing of robotic arm.

PubMed

Khasnobish, Anwesha; Pal, Monalisa; Sardar, Dwaipayan; Tibarewala, D N; Konar, Amit

2016-08-01

This work is a preliminary study towards developing an alternative communication channel for conveying shape information to aid in recognition of items when tactile perception is hindered. Tactile data, acquired during object exploration by sensor fitted robot arm, are processed to recognize four basic geometric shapes. Patterns representing each shape, classified from tactile data, are generated using micro-controller-driven vibration motors which vibrotactually stimulate users to convey the particular shape information. These motors are attached on the subject's arm and their psychological (verbal) responses are recorded to assess the competence of the system to convey shape information to the user in form of vibrotactile stimulations. Object shapes are classified from tactile data with an average accuracy of 95.21 %. Three successive sessions of shape recognition from vibrotactile pattern depicted learning of the stimulus from subjects' psychological response which increased from 75 to 95 %. This observation substantiates the learning of vibrotactile stimulation in user over the sessions which in turn increase the system efficacy. The tactile sensing module and vibrotactile pattern generating module are integrated to complete the system whose operation is analysed in real-time. Thus, the work demonstrates a successful implementation of the complete schema of artificial tactile sensing system for object-shape recognition through vibrotactile stimulations.

Distributional Effects of Word Frequency on Eye Fixation Durations

ERIC Educational Resources Information Center

Staub, Adrian; White, Sarah J.; Drieghe, Denis; Hollway, Elizabeth C.; Rayner, Keith

2010-01-01

Recent research using word recognition paradigms, such as lexical decision and speeded pronunciation, has investigated how a range of variables affect the location and shape of response time distributions, using both parametric and non-parametric techniques. In this article, we explore the distributional effects of a word frequency manipulation on…

Eye movements during object recognition in visual agnosia.

PubMed

Charles Leek, E; Patterson, Candy; Paul, Matthew A; Rafal, Robert; Cristino, Filipe

2012-07-01

This paper reports the first ever detailed study about eye movement patterns during single object recognition in visual agnosia. Eye movements were recorded in a patient with an integrative agnosic deficit during two recognition tasks: common object naming and novel object recognition memory. The patient showed normal directional biases in saccades and fixation dwell times in both tasks and was as likely as controls to fixate within object bounding contour regardless of recognition accuracy. In contrast, following initial saccades of similar amplitude to controls, the patient showed a bias for short saccades. In object naming, but not in recognition memory, the similarity of the spatial distributions of patient and control fixations was modulated by recognition accuracy. The study provides new evidence about how eye movements can be used to elucidate the functional impairments underlying object recognition deficits. We argue that the results reflect a breakdown in normal functional processes involved in the integration of shape information across object structure during the visual perception of shape. Copyright © 2012 Elsevier Ltd. All rights reserved.

Face-space: A unifying concept in face recognition research.

PubMed

Valentine, Tim; Lewis, Michael B; Hills, Peter J

2016-10-01

The concept of a multidimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to the development of face-space is explained, and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms, is reviewed. Face-space as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally, two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion, and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception.

Fully automatic segmentation of the femur from 3D-CT images using primitive shape recognition and statistical shape models.

PubMed

Ben Younes, Lassad; Nakajima, Yoshikazu; Saito, Toki

2014-03-01

Femur segmentation is well established and widely used in computer-assisted orthopedic surgery. However, most of the robust segmentation methods such as statistical shape models (SSM) require human intervention to provide an initial position for the SSM. In this paper, we propose to overcome this problem and provide a fully automatic femur segmentation method for CT images based on primitive shape recognition and SSM. Femur segmentation in CT scans was performed using primitive shape recognition based on a robust algorithm such as the Hough transform and RANdom SAmple Consensus. The proposed method is divided into 3 steps: (1) detection of the femoral head as sphere and the femoral shaft as cylinder in the SSM and the CT images, (2) rigid registration between primitives of SSM and CT image to initialize the SSM into the CT image, and (3) fitting of the SSM to the CT image edge using an affine transformation followed by a nonlinear fitting. The automated method provided good results even with a high number of outliers. The difference of segmentation error between the proposed automatic initialization method and a manual initialization method is less than 1 mm. The proposed method detects primitive shape position to initialize the SSM into the target image. Based on primitive shapes, this method overcomes the problem of inter-patient variability. Moreover, the results demonstrate that our method of primitive shape recognition can be used for 3D SSM initialization to achieve fully automatic segmentation of the femur.

Binding of intrinsic and extrinsic features in working memory.

PubMed

Ecker, Ullrich K H; Maybery, Murray; Zimmer, Hubert D

2013-02-01

There is ongoing debate concerning the mechanisms of feature binding in working memory. In particular, there is controversy regarding the extent to which these binding processes are automatic. The present article demonstrates that binding mechanisms differ depending on whether the to-be-integrated features are perceived as forming a coherent object. We presented a series of experiments that investigated the binding of color and shape, whereby color was either an intrinsic feature of the shape or an extrinsic feature of the shape's background. Results show that intrinsic color affected shape recognition, even when it was incidentally studied and irrelevant for the recognition task. In contrast, extrinsic color did not affect shape recognition, even when the association of color and shape was encoded and retrievable on demand. This strongly suggests that binding of intrinsic intra-item information but not extrinsic contextual information is obligatory in visual working memory. We highlight links to perception as well as implicit and explicit long-term memory, which suggest that the intrinsic-extrinsic dimension is a principle relevant to multiple domains of human cognition. 2013 APA, all rights reserved

Signalling product healthiness through symbolic package cues: Effects of package shape and goal congruence on consumer behaviour.

PubMed

van Ooijen, Iris; Fransen, Marieke L; Verlegh, Peeter W J; Smit, Edith G

2017-02-01

Three studies show that product packaging shape serves as a cue that communicates healthiness of food products. Inspired by embodiment accounts, we show that packaging that simulates a slim body shape acts as a symbolic cue for product healthiness (e.g., low in calories), as opposed to packaging that simulates a wide body shape. Furthermore, we show that the effect of slim package shape on consumer behaviour is goal dependent. Whereas simulation of a slim (vs. wide) body shape increases choice likelihood and product attitude when consumers have a health-relevant shopping goal, packaging shape does not affect these outcomes when consumers have a hedonic shopping goal. In Study 3, we adopt a realistic shopping paradigm using a shelf with authentic products, and find that a slim (as opposed to wide) package shape increases on-shelf product recognition and increases product attitude for healthy products. We discuss results and implications regarding product positioning and the packaging design process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed Central

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-01-01

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. PMID:29172273

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

The mere exposure effect is differentially sensitive to different judgment tasks.

PubMed

Seamon, J G; McKenna, P A; Binder, N

1998-03-01

The mere exposure effect is the increase in positive affect that results from the repeated exposure to previously novel stimuli. We sought to determine if judgments other than affective preference could reliably produce a mere exposure effect for two-dimensional random shapes. In two experiments, we found that brighter and darker judgments did not differentiate target from distracter shapes, liking judgments led to target selection greater than chance, and disliking judgments led to distracter selection greater than chance. These results for brighter, darker, and liking judgments were obtained regardless of whether shape recognition was greater (Experiment 1) or not greater (Experiment 2) than chance. Effects of prior exposure to novel shapes were reliably observed only for affective judgment tasks. These results are inconsistent with general predictions made by the nonspecific activation hypothesis, but not the affective primacy or perceptual fluency hypotheses which were discussed in terms of cognitive neuroscience research. Copyright 1998 Academic Press.

Learning through hand- or typewriting influences visual recognition of new graphic shapes: behavioral and functional imaging evidence.

PubMed

Longcamp, Marieke; Boucard, Céline; Gilhodes, Jean-Claude; Anton, Jean-Luc; Roth, Muriel; Nazarian, Bruno; Velay, Jean-Luc

2008-05-01

Fast and accurate visual recognition of single characters is crucial for efficient reading. We explored the possible contribution of writing memory to character recognition processes. We evaluated the ability of adults to discriminate new characters from their mirror images after being taught how to produce the characters either by traditional pen-and-paper writing or with a computer keyboard. After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favor of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.

Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Chunyuan; Stevens, Andrew J.; Chen, Changyou

2016-08-10

Learning the representation of shape cues in 2D & 3D objects for recognition is a fundamental task in computer vision. Deep neural networks (DNNs) have shown promising performance on this task. Due to the large variability of shapes, accurate recognition relies on good estimates of model uncertainty, ignored in traditional training of DNNs, typically learned via stochastic optimization. This paper leverages recent advances in stochastic gradient Markov Chain Monte Carlo (SG-MCMC) to learn weight uncertainty in DNNs. It yields principled Bayesian interpretations for the commonly used Dropout/DropConnect techniques and incorporates them into the SG-MCMC framework. Extensive experiments on 2D &more » 3D shape datasets and various DNN models demonstrate the superiority of the proposed approach over stochastic optimization. Our approach yields higher recognition accuracy when used in conjunction with Dropout and Batch-Normalization.« less

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

Hierachical Object Recognition Using Libraries of Parameterized Model Sub-Parts.

DTIC Science & Technology

1987-06-01

SketchI Structure Hierarchy Constrained Search 20. AUISTR ACT (Ce.ntU..w se reveres. 01411 at 00 OW 4MI 9smtilp Me"h aindo" This thesis describes the... theseU hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to...with different relative scaling, rotation, or translation than in the models. The approach taken in this thesis is to develop an object shape

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

NASA Astrophysics Data System (ADS)

Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; Ernastuti

2016-06-01

An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

Automatic detection and recognition of traffic signs in stereo images based on features and probabilistic neural networks

NASA Astrophysics Data System (ADS)

Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian

2008-04-01

Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.

Adaptation to Antifaces and the Perception of Correct Famous Identity in an Average Face

PubMed Central

Little, Anthony C.; Hancock, Peter J. B.; DeBruine, Lisa M.; Jones, Benedict C.

2011-01-01

Previous experiments have examined exposure to anti-identities (faces that possess traits opposite to an identity through a population average), finding that exposure to antifaces enhances recognition of the plus-identity images. Here we examine adaptation to antifaces using famous female celebrities. We demonstrate: that exposure to a color and shape transformed antiface of a celebrity increases the likelihood of perceiving the identity from which the antiface was manufactured in a composite face and that the effect shows size invariance (experiment 1), equivalent effects are seen in internet and laboratory-based studies (experiment 2), adaptation to shape-only antifaces has stronger effects on identity recognition than adaptation to color-only antifaces (experiment 3), and exposure to male versions of the antifaces does not influence the perception of female faces (experiment 4). Across these studies we found an effect of order where aftereffects were more pronounced in early than later trials. Overall, our studies delineate several aspects of identity aftereffects and support the proposal that identity is coded relative to other faces with special reference to a relatively sex-specific mean face representation. PMID:22363301

Interrupted Monosyllabic Words: The Effects of Ten Interruption Locations on Recognition Performance by Older Listeners with Sensorineural Hearing Loss.

PubMed

Wilson, Richard H; Sharrett, Kadie C

2017-01-01

Two previous experiments from our laboratory with 70 interrupted monosyllabic words demonstrated that recognition performance was influenced by the temporal location of the interruption pattern. The interruption pattern (10 interruptions/sec, 50% duty cycle) was always the same and referenced word onset; the only difference between the patterns was the temporal location of the on- and off-segments of the interruption cycle. In the first study, both young and older listeners obtained better recognition performances when the initial on-segment coincided with word onset than when the initial on-segment was delayed by 50 msec. The second experiment with 24 young listeners detailed recognition performance as the interruption pattern was incremented in 10-msec steps through the 0- to 90-msec onset range. Across the onset conditions, 95% of the functions were either flat or U-shaped. To define the effects that interruption pattern locations had on word recognition by older listeners with sensorineural hearing loss as the interruption pattern incremented, re: word onset, from 0 to 90 msec in 10-msec steps. A repeated-measures design with ten interruption patterns (onset conditions) and one uninterruption condition. Twenty-four older males (mean = 69.6 yr) with sensorineural hearing loss participated in two 1-hour sessions. The three-frequency pure-tone average was 24.0 dB HL and word recognition was ≥80% correct. Seventy consonant-vowel nucleus-consonant words formed the corpus of materials with 25 additional words used for practice. For each participant, the 700 interrupted stimuli (70 words by 10 onset conditions), the 70 words uninterrupted, and two practice lists each were randomized and recorded on compact disc in 33 tracks of 25 words each. The data were analyzed at the participant and word levels and compared to the results obtained earlier on 24 young listeners with normal hearing. The mean recognition performance on the 70 words uninterrupted was 91.0% with an overall mean performance on the ten interruption conditions of 63.2% (range: 57.9-69.3%), compared to 80.4% (range: 73.0-87.7%) obtained earlier on the young adults. The best performances were at the extremes of the onset conditions. Standard deviations ranged from 22.1% to 28.1% (24 participants) and from 9.2% to 12.8% (70 words). An arithmetic algorithm categorized the shapes of the psychometric functions across the ten onset conditions. With the older participants in the current study, 40% of the functions were flat, 41.4% were U-shaped, and 18.6% were inverted U-shaped, which compared favorably to the function shapes by the young listeners in the earlier study of 50.0%, 41.4%, and 8.6%, respectively. There were two words on which the older listeners had 40% better performances. Collectively, the data are orderly, but at the individual word or participant level, the data are somewhat volatile, which may reflect auditory processing differences between the participant groups. The diversity of recognition performances by the older listeners on the ten interruption conditions with each of the 70 words supports the notion that the term hearing loss is inclusive of processes well beyond the filtering produced by end-organ sensitivity deficits. American Academy of Audiology

Building Hierarchical Representations for Oracle Character and Sketch Recognition.

PubMed

Jun Guo; Changhu Wang; Roman-Rangel, Edgar; Hongyang Chao; Yong Rui

2016-01-01

In this paper, we study oracle character recognition and general sketch recognition. First, a data set of oracle characters, which are the oldest hieroglyphs in China yet remain a part of modern Chinese characters, is collected for analysis. Second, typical visual representations in shape- and sketch-related works are evaluated. We analyze the problems suffered when addressing these representations and determine several representation design criteria. Based on the analysis, we propose a novel hierarchical representation that combines a Gabor-related low-level representation and a sparse-encoder-related mid-level representation. Extensive experiments show the effectiveness of the proposed representation in both oracle character recognition and general sketch recognition. The proposed representation is also complementary to convolutional neural network (CNN)-based models. We introduce a solution to combine the proposed representation with CNN-based models, and achieve better performances over both approaches. This solution has beaten humans at recognizing general sketches.

Shape recognition of microbial cells by colloidal cell imprints

NASA Astrophysics Data System (ADS)

Borovička, Josef; Stoyanov, Simeon D.; Paunov, Vesselin N.

2013-08-01

We have engineered a class of colloids which can recognize the shape and size of targeted microbial cells and selectively bind to their surfaces. These imprinted colloid particles, which we called ``colloid antibodies'', were fabricated by partial fragmentation of silica shells obtained by templating the targeted microbial cells. We successfully demonstrated the shape and size recognition between such colloidal imprints and matching microbial cells. High percentage of binding events of colloidal imprints with the size matching target particles was achieved. We demonstrated selective binding of colloidal imprints to target microbial cells in a binary mixture of cells of different shapes and sizes, which also resulted in high binding selectivity. We explored the role of the electrostatic interactions between the target cells and their colloid imprints by pre-coating both of them with polyelectrolytes. Selective binding occurred predominantly in the case of opposite surface charges of the colloid cell imprint and the targeted cells. The mechanism of the recognition is based on the amplification of the surface adhesion in the case of shape and size match due to the increased contact area between the target cell and the colloidal imprint. We also tested the selective binding for colloid imprints of particles of fixed shape and varying sizes. The concept of cell recognition by colloid imprints could be used for development of colloid antibodies for shape-selective binding of microbes. Such colloid antibodies could be additionally functionalized with surface groups to enhance their binding efficiency to cells of specific shape and deliver a drug payload directly to their surface or allow them to be manipulated using external fields. They could benefit the pharmaceutical industry in developing selective antimicrobial therapies and formulations.

Geometric shapes inversion method of space targets by ISAR image segmentation

NASA Astrophysics Data System (ADS)

Huo, Chao-ying; Xing, Xiao-yu; Yin, Hong-cheng; Li, Chen-guang; Zeng, Xiang-yun; Xu, Gao-gui

2017-11-01

The geometric shape of target is an effective characteristic in the process of space targets recognition. This paper proposed a method of shape inversion of space target based on components segmentation from ISAR image. The Radon transformation, Hough transformation, K-means clustering, triangulation will be introduced into ISAR image processing. Firstly, we use Radon transformation and edge detection to extract space target's main body spindle and solar panel spindle from ISAR image. Then the targets' main body, solar panel, rectangular and circular antenna are segmented from ISAR image based on image detection theory. Finally, the sizes of every structural component are computed. The effectiveness of this method is verified using typical targets' simulation data.

A survey of visual preprocessing and shape representation techniques

NASA Technical Reports Server (NTRS)

Olshausen, Bruno A.

1988-01-01

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

Tactile agnosia. Underlying impairment and implications for normal tactile object recognition.

PubMed

Reed, C L; Caselli, R J; Farah, M J

1996-06-01

In a series of experimental investigations of a subject with a unilateral impairment of tactile object recognition without impaired tactile sensation, several issues were addressed. First, is tactile agnosia secondary to a general impairment of spatial cognition? On tests of spatial ability, including those directed at the same spatial integration process assumed to be taxed by tactile object recognition, the subject performed well, implying a more specific impairment of high level, modality specific tactile perception. Secondly, within the realm of high level tactile perception, is there a distinction between the ability to derive shape ('what') and spatial ('where') information? Our testing showed an impairment confined to shape perception. Thirdly, what aspects of shape perception are impaired in tactile agnosia? Our results indicate that despite accurate encoding of metric length and normal manual exploration strategies, the ability tactually to perceive objects with the impaired hand, deteriorated as the complexity of shape increased. In addition, asymmetrical performance was not found for other body surfaces (e.g. her feet). Our results suggest that tactile shape perception can be disrupted independent of general spatial ability, tactile spatial ability, manual shape exploration, or even the precise perception of metric length in the tactile modality.

Ball-scale based hierarchical multi-object recognition in 3D medical images

NASA Astrophysics Data System (ADS)

Bağci, Ulas; Udupa, Jayaram K.; Chen, Xinjian

2010-03-01

This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. This is achieved via the following set of key ideas: (a) A semi-automatic way of constructing a multi-object shape model assembly. (b) A novel strategy of encoding, via b-scale, the pose relationship between objects in the training images and their intensity patterns captured in b-scale images. (c) A hierarchical mechanism of positioning the model, in a one-shot way, in a given image from a knowledge of the learnt pose relationship and the b-scale image of the given image to be segmented. The evaluation results on a set of 20 routine clinical abdominal female and male CT data sets indicate the following: (1) Incorporating a large number of objects improves the recognition accuracy dramatically. (2) The recognition algorithm can be thought as a hierarchical framework such that quick replacement of the model assembly is defined as coarse recognition and delineation itself is known as finest recognition. (3) Scale yields useful information about the relationship between the model assembly and any given image such that the recognition results in a placement of the model close to the actual pose without doing any elaborate searches or optimization. (4) Effective object recognition can make delineation most accurate.

Influence of the width and cross-sectional shape of major connectors of maxillary dentures on the accuracy of speech production.

PubMed

Wada, Junichiro; Hideshima, Masayuki; Inukai, Shusuke; Matsuura, Hiroshi; Wakabayashi, Noriyuki

2014-01-01

To investigate the effects of the width and cross-sectional shape of the major connectors of maxillary dentures located in the middle area of the palate on the accuracy of phonetic output of consonants using an originally developed speech recognition system. Nine adults (4 males and 5 females, aged 24-26 years) with sound dentition were recruited. The following six sounds were considered: [∫i], [t∫i], [ɾi], [ni], [çi], and [ki]. The experimental connectors were fabricated to simulate bars (narrow, 8-mm width) and plates (wide, 20-mm width). Two types of cross-sectional shapes in the sagittal plane were specified: flat and plump edge. The appearance ratio of phonetic segment labels was calculated with the speech recognition system to indicate the accuracy of phonetic output. Statistical analysis was conducted using one-way ANOVA and Tukey's test. The mean appearance ratio of correct labels (MARC) significantly decreased for [ni] with the plump edge (narrow connector) and for [ki] with both the flat and plump edge (wide connectors). For [çi], the MARCs tended to be lower with flat plates. There were no significant differences for the other consonants. The width and cross-sectional shape of the connectors had limited effects on the articulation of consonants at the palate. © 2015 S. Karger AG, Basel.

Results using the OPAL strategy in Mandarin speaking cochlear implant recipients.

PubMed

Vandali, Andrew E; Dawson, Pam W; Arora, Komal

2017-01-01

To evaluate the effectiveness of an experimental pitch-coding strategy for improving recognition of Mandarin lexical tone in cochlear implant (CI) recipients. Adult CI recipients were tested on recognition of Mandarin tones in quiet and speech-shaped noise at a signal-to-noise ratio of +10 dB; Mandarin sentence speech-reception threshold (SRT) in speech-shaped noise; and pitch discrimination of synthetic complex-harmonic tones in quiet. Two versions of the experimental strategy were examined: (OPAL) linear (1:1) mapping of fundamental frequency (F0) to the coded modulation rate; and (OPAL+) transposed mapping of high F0s to a lower coded rate. Outcomes were compared to results using the clinical ACE™ strategy. Five Mandarin speaking users of Nucleus® cochlear implants. A small but significant benefit in recognition of lexical tones was observed using OPAL compared to ACE in noise, but not in quiet, and not for OPAL+ compared to ACE or OPAL in quiet or noise. Sentence SRTs were significantly better using OPAL+ and comparable using OPAL to those using ACE. No differences in pitch discrimination thresholds were observed across strategies. OPAL can provide benefits to Mandarin lexical tone recognition in moderately noisy conditions and preserve perception of Mandarin sentences in challenging noise conditions.

What Types of Visual Recognition Tasks Are Mediated by the Neural Subsystem that Subserves Face Recognition?

ERIC Educational Resources Information Center

Brooks, Brian E.; Cooper, Eric E.

2006-01-01

Three divided visual field experiments tested current hypotheses about the types of visual shape representation tasks that recruit the cognitive and neural mechanisms underlying face recognition. Experiment 1 found a right hemisphere advantage for subordinate but not basic-level face recognition. Experiment 2 found a right hemisphere advantage for…

Deep Neural Networks as a Computational Model for Human Shape Sensitivity

PubMed Central

Op de Beeck, Hans P.

2016-01-01

Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have largely failed. Recent studies suggest that state-of-the-art convolutional ‘deep’ neural networks (DNNs) capture important aspects of human object perception. We hypothesized that these successes might be partially related to a human-like representation of object shape. Here we demonstrate that sensitivity for shape features, characteristic to human and primate vision, emerges in DNNs when trained for generic object recognition from natural photographs. We show that these models explain human shape judgments for several benchmark behavioral and neural stimulus sets on which earlier models mostly failed. In particular, although never explicitly trained for such stimuli, DNNs develop acute sensitivity to minute variations in shape and to non-accidental properties that have long been implicated to form the basis for object recognition. Even more strikingly, when tested with a challenging stimulus set in which shape and category membership are dissociated, the most complex model architectures capture human shape sensitivity as well as some aspects of the category structure that emerges from human judgments. As a whole, these results indicate that convolutional neural networks not only learn physically correct representations of object categories but also develop perceptually accurate representational spaces of shapes. An even more complete model of human object representations might be in sight by training deep architectures for multiple tasks, which is so characteristic in human development. PMID:27124699

Shape, Color and the Other-Race Effect in the Infant Brain

ERIC Educational Resources Information Center

Balas, Benjamin; Westerlund, Alissa; Hung, Katherine; Nelson, Charles A., III

2011-01-01

The "other-race" effect describes the phenomenon in which faces are difficult to distinguish from one another if they belong to an ethnic or racial group to which the observer has had little exposure. Adult observers typically display multiple forms of recognition error for other-race faces, and infants exhibit behavioral evidence of a developing…

The Role of Experience during Childhood in Shaping the Other-Race Effect

ERIC Educational Resources Information Center

de Heering, Adelaide; de Liedekerke, Claire; Deboni, Malorie; Rossion, Bruno

2010-01-01

It is well known that adults' face recognition is characterized by an "other-race effect" (ORE; see Meissner & Brigham, 2001), but few studies have investigated this ORE during the development of the face processing system. Here we examined the role of experience with other-race faces during childhood by testing a group of 6- to…

Quantifying the effect of colorization enhancement on mammogram images

NASA Astrophysics Data System (ADS)

Wojnicki, Paul J.; Uyeda, Elizabeth; Micheli-Tzanakou, Evangelia

2002-04-01

Current methods of radiological displays provide only grayscale images of mammograms. The limitation of the image space to grayscale provides only luminance differences and textures as cues for object recognition within the image. However, color can be an important and significant cue in the detection of shapes and objects. Increasing detection ability allows the radiologist to interpret the images in more detail, improving object recognition and diagnostic accuracy. Color detection experiments using our stimulus system, have demonstrated that an observer can only detect an average of 140 levels of grayscale. An optimally colorized image can allow a user to distinguish 250 - 1000 different levels, hence increasing potential image feature detection by 2-7 times. By implementing a colorization map, which follows the luminance map of the original grayscale images, the luminance profile is preserved and color is isolated as the enhancement mechanism. The effect of this enhancement mechanism on the shape, frequency composition and statistical characteristics of the Visual Evoked Potential (VEP) are analyzed and presented. Thus, the effectiveness of the image colorization is measured quantitatively using the Visual Evoked Potential (VEP).

Effects of target shape and reflection on laser radar cross sections.

PubMed

Steinvall, O

2000-08-20

Laser radar cross sections have been evaluated for a number of ideal targets such as cones, spheres, paraboloids, and cylinders by use of different reflection characteristics. The time-independent cross section is the ratio of the cross section of one of these forms to that of a plate with the same maximum radius. The time-dependent laser radar cross section involves the impulse response from the object shape multiplied by the beam's transverse profile and the surface bidirectional reflection distribution function. It can be clearly seen that knowledge of the combined effect of object shape and reflection characteristics is important for determining the shape and the magnitude of the laser radar return. The results of this study are of interest for many laser radar applications such as ranging, three-dimensional imaging-modeling, tracking, antisensor lasers, and target recognition.

Effects of X-ray radiation on complex visual discrimination learning and social recognition memory in rats.

PubMed

Davis, Catherine M; Roma, Peter G; Armour, Elwood; Gooden, Virginia L; Brady, Joseph V; Weed, Michael R; Hienz, Robert D

2014-01-01

The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal). One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min), while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation.

Effects of X-Ray Radiation on Complex Visual Discrimination Learning and Social Recognition Memory in Rats

PubMed Central

Davis, Catherine M.; Roma, Peter G.; Armour, Elwood; Gooden, Virginia L.; Brady, Joseph V.; Weed, Michael R.; Hienz, Robert D.

2014-01-01

The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal). One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min), while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation. PMID:25099152

A model based method for recognizing psoas major muscles in torso CT images

NASA Astrophysics Data System (ADS)

Kamiya, Naoki; Zhou, Xiangrong; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi

2010-03-01

In aging societies, it is important to analyze age-related hypokinesia. A psoas major muscle has many important functional capabilities such as capacity of balance and posture control. These functions can be measured by its cross sectional area (CSA), volume, and thickness. However, these values are calculated manually in the clinical situation. The purpose of our study is to propose an automated recognition method of psoas major muscles in X-ray torso CT images. The proposed recognition process involves three steps: 1) determination of anatomical points such as the origin and insertion of the psoas major muscle, 2) generation of a shape model for the psoas major muscle, and 3) recognition of the psoas major muscles by use of the shape model. The model was built using quadratic function, and was fit to the anatomical center line of psoas major muscle. The shape model was generated using 20 CT cases and tested by 20 other CT cases. The applied database consisted of 12 male and 8 female cases from the ages of 40's to 80's. The average value of Jaccard similarity coefficient (JSC) values employed in the evaluation was 0.7. Our experimental results indicated that the proposed method was effective for a volumetric analysis and could be possible to be used for a quantitative measurement of psoas major muscles in CT images.

Impairment of nonverbal recognition in Alzheimer disease: a PET O-15 study.

PubMed

Anderson, K E; Brickman, A M; Flynn, J; Scarmeas, N; Van Heertum, R; Sackeim, H; Marder, K S; Bell, K; Moeller, J R; Stern, Y

2007-07-03

To characterize deficits in nonverbal recognition memory and functional brain changes associated with these deficits in Alzheimer disease (AD). Using O-15 PET, we studied 11 patients with AD and 17 cognitively intact elders during the combined encoding and retrieval periods of a nonverbal recognition task. Both task conditions involved recognition of line drawings of abstract shapes. In both conditions, subjects were first presented a list of shapes as study items, and then a list as test items, containing items from the study list and foils. In the titrated demand condition, the shape study list size (SLS) was adjusted prior to imaging so that each subject performed at approximately 75% recognition accuracy; difficulty during PET scanning in this condition was approximately matched across subjects. A control task was used in which SLS = 1 shape. During performance of the titrated demand condition, SLS averaged 4.55 (+/-1.86) shapes for patients with AD and 7.53 (+/-4.81) for healthy elderly subjects (p = 0.031). However, both groups of subjects were closely matched on performance in the titrated demand condition during PET scanning with 72.17% (+/-7.98%) correct for patients with AD and 72.25% (+/-7.03%) for elders (p = 0.979). PET results demonstrated that patients with AD showed greater mean differences between the titrated demand condition and control in areas including the left fusiform and inferior frontal regions (Brodmann areas 19 and 45). Relative fusiform and inferior frontal differences may reflect the Alzheimer disease (AD) patients' compensatory engagement of alternate brain regions. The strategy used by patients with AD is likely to be a general mechanism of compensation, rather than task-specific.

Lexical and age effects on word recognition in noise in normal-hearing children.

PubMed

Ren, Cuncun; Liu, Sha; Liu, Haihong; Kong, Ying; Liu, Xin; Li, Shujing

2015-12-01

The purposes of the present study were (1) to examine the lexical and age effects on word recognition of normal-hearing (NH) children in noise, and (2) to compare the word-recognition performance in noise to that in quiet listening conditions. Participants were 213 NH children (age ranged between 3 and 6 years old). Eighty-nine and 124 of the participants were tested in noise and quiet listening conditions, respectively. The Standard-Chinese Lexical Neighborhood Test, which contains lists of words in four lexical categories (i.e., dissyllablic easy (DE), dissyllablic hard (DH), monosyllable easy (ME), and monosyllable hard (MH)) was used to evaluate the Mandarin Chinese word recognition in speech spectrum-shaped noise (SSN) with a signal-to-noise ratio (SNR) of 0dB. A two-way repeated-measures analysis of variance was conducted to examine the lexical effects with syllable length and difficulty level as the main factors on word recognition in the quiet and noise listening conditions. The effects of age on word-recognition performance were examined using a regression model. The word-recognition performance in noise was significantly poorer than that in quiet and the individual variations in performance in noise were much greater than those in quiet. Word recognition scores showed that the lexical effects were significant in the SSN. Children scored higher with dissyllabic words than with monosyllabic words; "easy" words scored higher than "hard" words in the noise condition. The scores of the NH children in the SSN (SNR=0dB) for the DE, DH, ME, and MH words were 85.4, 65.9, 71.7, and 46.2% correct, respectively. The word-recognition performance also increased with age in each lexical category for the NH children tested in noise. Both age and lexical characteristics of words had significant influences on the performance of Mandarin-Chinese word recognition in noise. The lexical effects were more obvious under noise listening conditions than in quiet. The word-recognition performance in noise increased with age in NH children of 3-6 years old and had not reached plateau at 6 years of age in the NH children. Copyright © 2015. Published by Elsevier Ireland Ltd.

Developmental Differences in Shape Processing

ERIC Educational Resources Information Center

Sera, Maria D.; Gordon Millett, Katherine

2011-01-01

Considerable evidence indicates that shape similarity plays a major role in object recognition, identification and categorization. However, little is known about shape processing and its development. Across four experiments, we addressed two related questions. First, what makes objects similar in shape? Second, how does the processing of shape…

Object Recognition using Feature- and Color-Based Methods

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Stubberud, Allen

2008-01-01

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Static sign language recognition using 1D descriptors and neural networks

NASA Astrophysics Data System (ADS)

Solís, José F.; Toxqui, Carina; Padilla, Alfonso; Santiago, César

2012-10-01

A frame work for static sign language recognition using descriptors which represents 2D images in 1D data and artificial neural networks is presented in this work. The 1D descriptors were computed by two methods, first one consists in a correlation rotational operator.1 and second is based on contour analysis of hand shape. One of the main problems in sign language recognition is segmentation; most of papers report a special color in gloves or background for hand shape analysis. In order to avoid the use of gloves or special clothing, a thermal imaging camera was used to capture images. Static signs were picked up from 1 to 9 digits of American Sign Language, a multilayer perceptron reached 100% recognition with cross-validation.

When apperceptive agnosia is explained by a deficit of primary visual processing.

PubMed

Serino, Andrea; Cecere, Roberto; Dundon, Neil; Bertini, Caterina; Sanchez-Castaneda, Cristina; Làdavas, Elisabetta

2014-03-01

Visual agnosia is a deficit in shape perception, affecting figure, object, face and letter recognition. Agnosia is usually attributed to lesions to high-order modules of the visual system, which combine visual cues to represent the shape of objects. However, most of previously reported agnosia cases presented visual field (VF) defects and poor primary visual processing. The present case-study aims to verify whether form agnosia could be explained by a deficit in basic visual functions, rather that by a deficit in high-order shape recognition. Patient SDV suffered a bilateral lesion of the occipital cortex due to anoxia. When tested, he could navigate, interact with others, and was autonomous in daily life activities. However, he could not recognize objects from drawings and figures, read or recognize familiar faces. He was able to recognize objects by touch and people from their voice. Assessments of visual functions showed blindness at the centre of the VF, up to almost 5°, bilaterally, with better stimulus detection in the periphery. Colour and motion perception was preserved. Psychophysical experiments showed that SDV's visual recognition deficits were not explained by poor spatial acuity or by the crowding effect. Rather a severe deficit in line orientation processing might be a key mechanism explaining SDV's agnosia. Line orientation processing is a basic function of primary visual cortex neurons, necessary for detecting "edges" of visual stimuli to build up a "primal sketch" for object recognition. We propose, therefore, that some forms of visual agnosia may be explained by deficits in basic visual functions due to widespread lesions of the primary visual areas, affecting primary levels of visual processing. Copyright © 2013 Elsevier Ltd. All rights reserved.

New Approaches Towards Recognition of Nucleic Acid Triple Helices

PubMed Central

Arya, Dev P.

2012-01-01

We show that groove recognition of nucleic acid triple helices can be achieved with aminosugars. Among these aminosugars, neomycin is the most effective aminoglycoside (groove binder) for stabilizing a DNA triple helix. It stabilizes both the T·A·T triplex and mixed-base DNA triplexes better than known DNA minor groove binders (which usually destabilize the triplex) and polyamines. Neomycin selectively stabilizes the triplex (T·A·T and mixed base) without any effect on the DNA duplex. The selectivity of neomycin likely originates from its potential and shape complementarity to the triplex Watson–Hoogsteen groove, making it the first molecule that selectively recognizes a triplex groove over a duplex groove. The groove recognition of aminoglycosides is not limited to DNA triplexes, but also extends to RNA and hybrid triple helical structures. Intercalator–neomycin conjugates are shown to simultaneously probe the base stacking and groove surface in the DNA triplex. Calorimetric and spectrosocopic studies allow the quantification of the effect of surface area of the intercalating moiety on binding to the triplex. These studies outline a novel approach to the recognition of DNA triplexes that incorporates the use of non-competing binding sites. These principles of dual recognition should be applicable to the design of ligands that can bind any given nucleic acid target with nanomolar affinities and with high selectivity. PMID:21073199

Measuring the effects of spectral smearing and enhancement on speech recognition in noise for adults and children

PubMed Central

Nittrouer, Susan; Tarr, Eric; Wucinich, Taylor; Moberly, Aaron C.; Lowenstein, Joanna H.

2015-01-01

Broadened auditory filters associated with sensorineural hearing loss have clearly been shown to diminish speech recognition in noise for adults, but far less is known about potential effects for children. This study examined speech recognition in noise for adults and children using simulated auditory filters of different widths. Specifically, 5 groups (20 listeners each) of adults or children (5 and 7 yrs), were asked to recognize sentences in speech-shaped noise. Seven-year-olds listened at 0 dB signal-to-noise ratio (SNR) only; 5-yr-olds listened at +3 or 0 dB SNR; and adults listened at 0 or −3 dB SNR. Sentence materials were processed both to smear the speech spectrum (i.e., simulate broadened filters), and to enhance the spectrum (i.e., simulate narrowed filters). Results showed: (1) Spectral smearing diminished recognition for listeners of all ages; (2) spectral enhancement did not improve recognition, and in fact diminished it somewhat; and (3) interactions were observed between smearing and SNR, but only for adults. That interaction made age effects difficult to gauge. Nonetheless, it was concluded that efforts to diagnose the extent of broadening of auditory filters and to develop techniques to correct this condition could benefit patients with hearing loss, especially children. PMID:25920851

Face recognition from unconstrained three-dimensional face images using multitask sparse representation

NASA Astrophysics Data System (ADS)

Bentaieb, Samia; Ouamri, Abdelaziz; Nait-Ali, Amine; Keche, Mokhtar

2018-01-01

We propose and evaluate a three-dimensional (3D) face recognition approach that applies the speeded up robust feature (SURF) algorithm to the depth representation of shape index map, under real-world conditions, using only a single gallery sample for each subject. First, the 3D scans are preprocessed, then SURF is applied on the shape index map to find interest points and their descriptors. Each 3D face scan is represented by keypoints descriptors, and a large dictionary is built from all the gallery descriptors. At the recognition step, descriptors of a probe face scan are sparsely represented by the dictionary. A multitask sparse representation classification is used to determine the identity of each probe face. The feasibility of the approach that uses the SURF algorithm on the shape index map for face identification/authentication is checked through an experimental investigation conducted on Bosphorus, University of Milano Bicocca, and CASIA 3D datasets. It achieves an overall rank one recognition rate of 97.75%, 80.85%, and 95.12%, respectively, on these datasets.

Finger vein recognition with personalized feature selection.

PubMed

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-08-22

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Finger Vein Recognition with Personalized Feature Selection

PubMed Central

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-01-01

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG. PMID:23974154

Minimizing Skin Color Differences Does Not Eliminate the Own-Race Recognition Advantage in Infants

PubMed Central

Anzures, Gizelle; Pascalis, Olivier; Quinn, Paul C.; Slater, Alan M.; Lee, Kang

2011-01-01

An abundance of experience with own-race faces and limited to no experience with other-race faces has been associated with better recognition memory for own-race faces in infants, children, and adults. This study investigated the developmental origins of this other-race effect (ORE) by examining the role of a salient perceptual property of faces—that of skin color. Six- and 9-month-olds’ recognition memory for own- and other-race faces was examined using infant-controlled habituation and visual-paired comparison at test. Infants were shown own- or other-race faces in color or with skin color cues minimized in grayscale images. Results for the color stimuli replicated previous findings that infants show an ORE in face recognition memory. Results for the grayscale stimuli showed that even when a salient perceptual cue to race, such as skin color information, is minimized, 6- to 9-month-olds, nonetheless, show an ORE in their face recognition memory. Infants’ use of shape-based and configural cues for face recognition is discussed. PMID:22039335

Subjectively Interpreted Shape Dimensions as Privileged and Orthogonal Axes in Mental Shape Space

ERIC Educational Resources Information Center

Ons, Bart; De Baene, Wouter; Wagemans, Johan

2011-01-01

The shape of an object is fundamental in object recognition but it is still an open issue to what extent shape differences are perceived analytically (i.e., by the dimensional structure of the shapes) or holistically (i.e., by the overall similarity of the shapes). The dimensional structure of a stimulus is available in a primary stage of…

Adaptive Hybrid Picture Coding. Volume 2.

DTIC Science & Technology

1985-02-01

ooo5 V.a Measurement Vector ..eho..............57 V.b Size Variable o .entroi* Vector .......... .- 59 V * c Shape Vector .Ř 0-60o oe 6 I V~d...the Program for the Adaptive Line of Sight Method .i.. 18.. o ... .... .... 1 B Details of the Feature Vector FormationProgram .. o ...oo..-....- .122 C ...shape recognition is analogous to recognition of curves in space. Therefore, well known concepts and theorems from differential geometry can be 34 . o

ATR applications of minimax entropy models of texture and shape

NASA Astrophysics Data System (ADS)

Zhu, Song-Chun; Yuille, Alan L.; Lanterman, Aaron D.

2001-10-01

Concepts from information theory have recently found favor in both the mainstream computer vision community and the military automatic target recognition community. In the computer vision literature, the principles of minimax entropy learning theory have been used to generate rich probabilitistic models of texture and shape. In addition, the method of types and large deviation theory has permitted the difficulty of various texture and shape recognition tasks to be characterized by 'order parameters' that determine how fundamentally vexing a task is, independent of the particular algorithm used. These information-theoretic techniques have been demonstrated using traditional visual imagery in applications such as simulating cheetah skin textures and such as finding roads in aerial imagery. We discuss their application to problems in the specific application domain of automatic target recognition using infrared imagery. We also review recent theoretical and algorithmic developments which permit learning minimax entropy texture models for infrared textures in reasonable timeframes.

Shape analysis modeling for character recognition

NASA Astrophysics Data System (ADS)

Khan, Nadeem A. M.; Hegt, Hans A.

1998-10-01

Optimal shape modeling of character-classes is crucial for achieving high performance on recognition of mixed-font, hand-written or (and) poor quality text. A novel scheme is presented in this regard focusing on constructing such structural models that can be hierarchically examined. These models utilize a certain `well-thought' set of shape primitives. They are simplified enough to ignore the inter- class variations in font-type or writing style yet retaining enough details for discrimination between the samples of the similar classes. Thus the number of models per class required can be kept minimal without sacrificing the recognition accuracy. In this connection a flexible multi- stage matching scheme exploiting the proposed modeling is also described. This leads to a system which is robust against various distortions and degradation including those related to cases of touching and broken characters. Finally, we present some examples and test results as a proof-of- concept demonstrating the validity and the robustness of the approach.

Developmental Origins of the Other-Race Effect

PubMed Central

Anzures, Gizelle; Quinn, Paul C.; Pascalis, Olivier; Slater, Alan M.; Tanaka, James W.; Lee, Kang

2013-01-01

The other-race effect (ORE) in face recognition refers to better recognition memory for faces of one’s own race than faces of another race—a common phenomenon among individuals living in primarily mono-racial societies. In this article, we review findings suggesting that early visual and sociocultural experiences shape one’s processing of familiar and unfamiliar race classes and give rise to the ORE within the 1st year of life. However, despite its early development, the ORE can be prevented, attenuated, and even reversed given experience with a novel race class. Social implications of the ORE are discussed in relation to development of race-based preferences for social partners and racial prejudices. PMID:24049246

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

NASA Astrophysics Data System (ADS)

Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

2016-06-01

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Localization and recognition of traffic signs for automated vehicle control systems

NASA Astrophysics Data System (ADS)

Zadeh, Mahmoud M.; Kasvand, T.; Suen, Ching Y.

1998-01-01

We present a computer vision system for detection and recognition of traffic signs. Such systems are required to assist drivers and for guidance and control of autonomous vehicles on roads and city streets. For experiments we use sequences of digitized photographs and off-line analysis. The system contains four stages. First, region segmentation based on color pixel classification called SRSM. SRSM limits the search to regions of interest in the scene. Second, we use edge tracing to find parts of outer edges of signs which are circular or straight, corresponding to the geometrical shapes of traffic signs. The third step is geometrical analysis of the outer edge and preliminary recognition of each candidate region, which may be a potential traffic sign. The final step in recognition uses color combinations within each region and model matching. This system maybe used for recognition of other types of objects, provided that the geometrical shape and color content remain reasonably constant. The method is reliable, easy to implement, and fast, This differs form the road signs recognition method in the PROMETEUS. The overall structure of the approach is sketched.

Songbirds use spectral shape, not pitch, for sound pattern recognition

PubMed Central

Bregman, Micah R.; Patel, Aniruddh D.; Gentner, Timothy Q.

2016-01-01

Humans easily recognize “transposed” musical melodies shifted up or down in log frequency. Surprisingly, songbirds seem to lack this capacity, although they can learn to recognize human melodies and use complex acoustic sequences for communication. Decades of research have led to the widespread belief that songbirds, unlike humans, are strongly biased to use absolute pitch (AP) in melody recognition. This work relies almost exclusively on acoustically simple stimuli that may belie sensitivities to more complex spectral features. Here, we investigate melody recognition in a species of songbird, the European Starling (Sturnus vulgaris), using tone sequences that vary in both pitch and timbre. We find that small manipulations altering either pitch or timbre independently can drive melody recognition to chance, suggesting that both percepts are poor descriptors of the perceptual cues used by birds for this task. Instead we show that melody recognition can generalize even in the absence of pitch, as long as the spectral shapes of the constituent tones are preserved. These results challenge conventional views regarding the use of pitch cues in nonhuman auditory sequence recognition. PMID:26811447

Limited receptive area neural classifier for recognition of swallowing sounds using continuous wavelet transform.

PubMed

Makeyev, Oleksandr; Sazonov, Edward; Schuckers, Stephanie; Lopez-Meyer, Paulo; Melanson, Ed; Neuman, Michael

2007-01-01

In this paper we propose a sound recognition technique based on the limited receptive area (LIRA) neural classifier and continuous wavelet transform (CWT). LIRA neural classifier was developed as a multipurpose image recognition system. Previous tests of LIRA demonstrated good results in different image recognition tasks including: handwritten digit recognition, face recognition, metal surface texture recognition, and micro work piece shape recognition. We propose a sound recognition technique where scalograms of sound instances serve as inputs of the LIRA neural classifier. The methodology was tested in recognition of swallowing sounds. Swallowing sound recognition may be employed in systems for automated swallowing assessment and diagnosis of swallowing disorders. The experimental results suggest high efficiency and reliability of the proposed approach.

Ground target recognition using rectangle estimation.

PubMed

Grönwall, Christina; Gustafsson, Fredrik; Millnert, Mille

2006-11-01

We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

Image recognition on raw and processed potato detection: a review

NASA Astrophysics Data System (ADS)

Qi, Yan-nan; Lü, Cheng-xu; Zhang, Jun-ning; Li, Ya-shuo; Zeng, Zhen; Mao, Wen-hua; Jiang, Han-lu; Yang, Bing-nan

2018-02-01

Objective: Chinese potato staple food strategy clearly pointed out the need to improve potato processing, while the bottleneck of this strategy is technology and equipment of selection of appropriate raw and processed potato. The purpose of this paper is to summarize the advanced raw and processed potato detection methods. Method: According to consult research literatures in the field of image recognition based potato quality detection, including the shape, weight, mechanical damage, germination, greening, black heart, scab potato etc., the development and direction of this field were summarized in this paper. Result: In order to obtain whole potato surface information, the hardware was built by the synchronous of image sensor and conveyor belt to achieve multi-angle images of a single potato. Researches on image recognition of potato shape are popular and mature, including qualitative discrimination on abnormal and sound potato, and even round and oval potato, with the recognition accuracy of more than 83%. Weight is an important indicator for potato grading, and the image classification accuracy presents more than 93%. The image recognition of potato mechanical damage focuses on qualitative identification, with the main affecting factors of damage shape and damage time. The image recognition of potato germination usually uses potato surface image and edge germination point. Both of the qualitative and quantitative detection of green potato have been researched, currently scab and blackheart image recognition need to be operated using the stable detection environment or specific device. The image recognition of processed potato mainly focuses on potato chips, slices and fries, etc. Conclusion: image recognition as a food rapid detection tool have been widely researched on the area of raw and processed potato quality analyses, its technique and equipment have the potential for commercialization in short term, to meet to the strategy demand of development potato as staple food in China.

Shape shifting: Local landmarks interfere with navigation by, and recognition of, global shape.

PubMed

Buckley, Matthew G; Smith, Alastair D; Haselgrove, Mark

2014-03-01

An influential theory of spatial navigation states that the boundary shape of an environment is preferentially encoded over and above other spatial cues, such that it is impervious to interference from alternative sources of information. We explored this claim with 3 intradimensional-extradimensional shift experiments, designed to examine the interaction of landmark and geometric features of the environment in a virtual navigation task. In Experiments 1 and 2, participants were first required to find a hidden goal using information provided by the shape of the arena or landmarks integrated into the arena boundary (Experiment 1) or within the arena itself (Experiment 2). Participants were then transferred to a different-shaped arena that contained novel landmarks and were again required to find a hidden goal. In both experiments, participants who were navigating on the basis of cues that were from the same dimension that was previously relevant (intradimensional shift) learned to find the goal significantly faster than participants who were navigating on the basis of cues that were from a dimension that was previously irrelevant (extradimensional shift). This suggests that shape information does not hold special status when learning about an environment. Experiment 3 replicated Experiment 2 and also assessed participants' recognition of the global shape of the navigated arenas. Recognition was attenuated when landmarks were relevant to navigation throughout the experiment. The results of these experiments are discussed in terms of associative and non-associative theories of spatial learning.

Regulation Effects by Programmed Molecules for Transcription-Based Diagnostic Automata towards Therapeutic Use

NASA Astrophysics Data System (ADS)

Hirabayashi, Miki; Ohashi, Hirotada; Kubo, Tai

We have presented experimental analysis on the controllability of our transcription-based diagnostic biomolecular automata by programmed molecules. Focusing on the noninvasive transcriptome diagnosis by salivary mRNAs, we already proposed the novel concept of diagnostic device using DNA computation. This system consists of the main computational element which has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by the recognition of disease-related biomarkers. We utilize the transcription of malachite green aptamer sequence triggered by the target recognition for observation of detection. This algorithm makes it possible to release RNA-aptamer drugs multiply, different from the digestion-based systems by the restriction enzyme which was proposed previously, for the in-vivo use, however, the controllability of aptamer release is not enough at the previous stage. In this paper, we verified the regulation effect on aptamer transcription by programmed molecules in basic conditions towards the developm! ent of therapeutic automata. These results would bring us one step closer to the realization of new intelligent diagnostic and therapeutic automata based on molecular circuits.

Biometric recognition using 3D ear shape.

PubMed

Yan, Ping; Bowyer, Kevin W

2007-08-01

Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and 3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario on a database of 415 subjects and 1,386 total probes.

Aging and visual 3-D shape recognition from motion.

PubMed

Norman, J Farley; Adkins, Olivia C; Dowell, Catherine J; Hoyng, Stevie C; Shain, Lindsey M; Pedersen, Lauren E; Kinnard, Jonathan D; Higginbotham, Alexia J; Gilliam, Ashley N

2017-11-01

Two experiments were conducted to evaluate the ability of younger and older adults to recognize 3-D object shape from patterns of optical motion. In Experiment 1, participants were required to identify dotted surfaces that rotated in depth (i.e., surface structure portrayed using the kinetic depth effect). The task difficulty was manipulated by limiting the surface point lifetimes within the stimulus apparent motion sequences. In Experiment 2, the participants identified solid, naturally shaped objects (replicas of bell peppers, Capsicum annuum) that were defined by occlusion boundary contours, patterns of specular highlights, or combined optical patterns containing both boundary contours and specular highlights. Significant and adverse effects of increased age were found in both experiments. Despite the fact that previous research has found that increases in age do not reduce solid shape discrimination, our current results indicated that the same conclusion does not hold for shape identification. We demonstrated that aging results in a reduction in the ability to visually recognize 3-D shape independent of how the 3-D structure is defined (motions of isolated points, deformations of smooth optical fields containing specular highlights, etc.).

Vibration mode shape recognition using image processing

NASA Astrophysics Data System (ADS)

Wang, Weizhuo; Mottershead, John E.; Mares, Cristinel

2009-10-01

Currently the most widely used method for comparing mode shapes from finite elements and experimental measurements is the modal assurance criterion (MAC), which can be interpreted as the cosine of the angle between the numerical and measured eigenvectors. However, the eigenvectors only contain the displacement of discrete coordinates, so that the MAC index carries no explicit information on shape features. New techniques, based upon the well-developed philosophies of image processing (IP) and pattern recognition (PR) are considered in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD) are the most popular shape descriptors due to their outstanding properties in IP and PR. These include (1) for the ZMD-rotational invariance, expression and computing efficiency, ease of reconstruction and robustness to noise; (2) for the FD—separation of the global shape and shape-details by low and high frequency components, respectively, invariance under geometric transformation; (3) for the WD—multi-scale representation and local feature detection. Once a shape descriptor has been adopted, the comparison of mode shapes is transformed to a comparison of multidimensional shape feature vectors. Deterministic and statistical methods are presented. The deterministic problem of measuring the degree of similarity between two mode shapes (possibly one from a vibration test and the other from a finite element model) may be carried out using Pearson's correlation. Similar shape feature vectors may be arranged in clusters separated by Euclidian distances in the feature space. In the statistical analysis we are typically concerned with the classification of a test mode shape according to clusters of shape feature vectors obtained from a randomised finite element model. The dimension of the statistical problem may often be reduced by principal component analysis. Then, in addition to the Euclidian distance, the Mahalanobis distance, defining the separation of the test point from the cluster in terms of its standard deviation, becomes an important measure. Bayesian decision theory may be applied to formally minimise the risk of misclassification of the test shape feature vector. In this paper the ZMD is applied to the problem of mode shape recognition for a circular plate. Results show that the ZMD has considerable advantages over the traditional MAC index when identifying the cyclically symmetric mode shapes that occur in axisymmetric structures at identical frequencies. Mode shape recognition of rectangular plates is carried out by the FD. Also, the WD is applied to the problem of recognising the mode shapes in the thin and thick regions of a plate with different thicknesses. It shows the benefit of using the WD to identify mode-shapes having both local and global components. The comparison and classification of mode shapes using IP and PR provides a 'toolkit' to complement the conventional MAC approach. The selection of a particular shape descriptor and classification method will depend upon the problem in hand and the experience of the analyst.

Experimental strain modal analysis for beam-like structure by using distributed fiber optics and its damage detection

NASA Astrophysics Data System (ADS)

Cheng, Liangliang; Busca, Giorgio; Cigada, Alfredo

2017-07-01

Modal analysis is commonly considered as an effective tool to obtain the intrinsic characteristics of structures including natural frequencies, modal damping ratios, and mode shapes, which are significant indicators for monitoring the health status of engineering structures. The complex mode indicator function (CMIF) can be regarded as an effective numerical tool to perform modal analysis. In this paper, experimental strain modal analysis based on the CMIF has been introduced. Moreover, a distributed fiber-optic sensor, as a dense measuring device, has been applied to acquire strain data along a beam surface. Thanks to the dense spatial resolution of the distributed fiber optics, more detailed mode shapes could be obtained. In order to test the effectiveness of the method, a mass lump—considered as a linear damage component—has been attached to the surface of the beam, and damage detection based on strain mode shape has been carried out. The results manifest that strain modal parameters can be estimated effectively by utilizing the CMIF based on the corresponding simulations and experiments. Furthermore, damage detection based on strain mode shapes benefits from the accuracy of strain mode shape recognition and the excellent performance of the distributed fiber optics.

The Struggle for Identity in Today's Schools: Cultural Recognition in a Time of Increasing Diversity

ERIC Educational Resources Information Center

Jenlink, Patrick M., Ed; Townes, Faye Hicks, Ed

2009-01-01

The "Struggle for Identity in Today's Schools" examines cultural recognition and the struggle for identity in America's schools. In particular, the contributing authors focus on the recognition and misrecognition as antagonistic cultural forces that work to shape, and at times distort identity. What surfaces throughout the chapters are two lessons…

Global shape recognition is modulated by the spatial distance of local elements--evidence from simultanagnosia.

PubMed

Huberle, Elisabeth; Karnath, Hans-Otto

2006-01-01

Simultanagnosia is a rare deficit that impairs individuals in perceiving several objects at the same time. It is usually observed following bilateral parieto-occipital brain damage. Despite the restrictions in perceiving the global aspect of a scene, processing of individual objects remains unaffected. The mechanisms underlying simultanagnosia are not well understood. Previous findings indicated that the integration of multiple objects into a holistic representation of the environment is not impossible per se, but might depend on the spatial relationship between individual objects. The present study examined the influence of inter-element distances between individual objects on the recognition of global shapes in two patients with simultanagnosia. We presented Navon hierarchical letter stimuli with different inter-element distances between letters at the Local Scale. Improved recognition at the Global Scale was observed in both patients by reducing the inter-element distance. Global shape recognition in simultanagnosia thus seems to be modulated by the spatial distance of local elements and does not appear to be an all-or-nothing phenomenon depending on spatial continuity. The findings seem to argue against a deficit in visual working memory capacity as the primary deficit in simultanagnosia. However, further research is necessary to investigate alternative interpretations.

Automatic lip reading by using multimodal visual features

NASA Astrophysics Data System (ADS)

Takahashi, Shohei; Ohya, Jun

2013-12-01

Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

Post processing for offline Chinese handwritten character string recognition

NASA Astrophysics Data System (ADS)

Wang, YanWei; Ding, XiaoQing; Liu, ChangSong

2012-01-01

Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition. Due to the free writing style, large variability in character shapes and different geometric characteristics, Chinese handwritten character string recognition is a challenging problem to deal with. However, among the current methods over-segmentation and merging method which integrates geometric information, character recognition information and contextual information, shows a promising result. It is found experimentally that a large part of errors are segmentation error and mainly occur around non-Chinese characters. In a Chinese character string, there are not only wide characters namely Chinese characters, but also narrow characters like digits and letters of the alphabet. The segmentation error is mainly caused by uniform geometric model imposed on all segmented candidate characters. To solve this problem, post processing is employed to improve recognition accuracy of narrow characters. On one hand, multi-geometric models are established for wide characters and narrow characters respectively. Under multi-geometric models narrow characters are not prone to be merged. On the other hand, top rank recognition results of candidate paths are integrated to boost final recognition of narrow characters. The post processing method is investigated on two datasets, in total 1405 handwritten address strings. The wide character recognition accuracy has been improved lightly and narrow character recognition accuracy has been increased up by 10.41% and 10.03% respectively. It indicates that the post processing method is effective to improve recognition accuracy of narrow characters.

From Caregivers to Peers: Puberty Shapes Human Face Perception.

PubMed

Picci, Giorgia; Scherf, K Suzanne

2016-11-01

Puberty prepares mammals to sexually reproduce during adolescence. It is also hypothesized to invoke a social metamorphosis that prepares adolescents to take on adult social roles. We provide the first evidence to support this hypothesis in humans and show that pubertal development retunes the face-processing system from a caregiver bias to a peer bias. Prior to puberty, children exhibit enhanced recognition for adult female faces. With puberty, superior recognition emerges for peer faces that match one's pubertal status. As puberty progresses, so does the peer recognition bias. Adolescents become better at recognizing faces with a pubertal status similar to their own. These findings reconceptualize the adolescent "dip" in face recognition by showing that it is a recalibration of the face-processing system away from caregivers toward peers. Thus, in addition to preparing the physical body for sexual reproduction, puberty shapes the perceptual system for processing the social world in new ways. © The Author(s) 2016.

Cesium cation templated selective synthesis of a "cone-shaped" sugar macrotricyclic cryptand: A dual anion-cation molecular recognition of potassium tartrate.

PubMed

Porwanski, S; Moretti, F; Dumarcay-Charbonnier, F; Marsura, A

2016-05-01

Cesium templated Staudinger-aza-Wittig tandem reaction (S.A.W.) has been used in the synthesis of a bis-diazacrown-bis-cellobiosyl-tetra-ureido cryptand. A novel macrotricyclic compound having a "cone-shaped" configuration was selectively obtained. Additionally, first results on potential recognition properties of the cryptand are also given. Copyright © 2015 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Transformations in the Recognition of Visual Forms

ERIC Educational Resources Information Center

Charness, Neil; Bregman, Albert S.

1973-01-01

In a study which required college students to learn to recognize four flexible plastic shapes photographed on different backgrounds from different angles, the importance of a context-rich environment for the learning and recognition of visual patterns was illustrated. (Author)

The review and results of different methods for facial recognition

NASA Astrophysics Data System (ADS)

Le, Yifan

2017-09-01

In recent years, facial recognition draws much attention due to its wide potential applications. As a unique technology in Biometric Identification, facial recognition represents a significant improvement since it could be operated without cooperation of people under detection. Hence, facial recognition will be taken into defense system, medical detection, human behavior understanding, etc. Several theories and methods have been established to make progress in facial recognition: (1) A novel two-stage facial landmark localization method is proposed which has more accurate facial localization effect under specific database; (2) A statistical face frontalization method is proposed which outperforms state-of-the-art methods for face landmark localization; (3) It proposes a general facial landmark detection algorithm to handle images with severe occlusion and images with large head poses; (4) There are three methods proposed on Face Alignment including shape augmented regression method, pose-indexed based multi-view method and a learning based method via regressing local binary features. The aim of this paper is to analyze previous work of different aspects in facial recognition, focusing on concrete method and performance under various databases. In addition, some improvement measures and suggestions in potential applications will be put forward.

Cognitive object recognition system (CORS)

NASA Astrophysics Data System (ADS)

Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

2010-04-01

We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

Chinese wine classification system based on micrograph using combination of shape and structure features

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

NASA Astrophysics Data System (ADS)

Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2014-03-01

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

Crowding and Cognitive Development: The Mediating Role of Maternal Responsiveness among 36-Month-Old Children

ERIC Educational Resources Information Center

Evans, Gary W.; Ricciuti, Henry N.; Hope, Steven; Schoon, Ingrid; Bradley, Robert H.; Corwyn, Robert F.; Hazan, Cindy

2010-01-01

Residential crowding in both U.S. and U.K. samples of 36-month-old children is related concurrently to the Bracken scale, a standard index of early cognitive development skills including letter and color identification, shape recognition, and elementary numeric comprehension. In the U.S. sample, these effects also replicate prospectively.…

Traffic sign recognition based on a context-aware scale-invariant feature transform approach

NASA Astrophysics Data System (ADS)

Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

2013-10-01

A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

The Limits of Shape Recognition following Late Emergence from Blindness.

PubMed

McKyton, Ayelet; Ben-Zion, Itay; Doron, Ravid; Zohary, Ehud

2015-09-21

Visual object recognition develops during the first years of life. But what if one is deprived of vision during early post-natal development? Shape information is extracted using both low-level cues (e.g., intensity- or color-based contours) and more complex algorithms that are largely based on inference assumptions (e.g., illumination is from above, objects are often partially occluded). Previous studies, testing visual acuity using a 2D shape-identification task (Lea symbols), indicate that contour-based shape recognition can improve with visual experience, even after years of visual deprivation from birth. We hypothesized that this may generalize to other low-level cues (shape, size, and color), but not to mid-level functions (e.g., 3D shape from shading) that might require prior visual knowledge. To that end, we studied a unique group of subjects in Ethiopia that suffered from an early manifestation of dense bilateral cataracts and were surgically treated only years later. Our results suggest that the newly sighted rapidly acquire the ability to recognize an odd element within an array, on the basis of color, size, or shape differences. However, they are generally unable to find the odd shape on the basis of illusory contours, shading, or occlusion relationships. Little recovery of these mid-level functions is seen within 1 year post-operation. We find that visual performance using low-level cues is relatively robust to prolonged deprivation from birth. However, the use of pictorial depth cues to infer 3D structure from the 2D retinal image is highly susceptible to early and prolonged visual deprivation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Generalization between canonical and non-canonical views in object recognition

PubMed Central

Ghose, Tandra; Liu, Zili

2013-01-01

Viewpoint generalization in object recognition is the process that allows recognition of a given 3D object from many different viewpoints despite variations in its 2D projections. We used the canonical view effects as a foundation to empirically test the validity of a major theory in object recognition, the view-approximation model (Poggio & Edelman, 1990). This model predicts that generalization should be better when an object is first seen from a non-canonical view and then a canonical view than when seen in the reversed order. We also manipulated object similarity to study the degree to which this view generalization was constrained by shape details and task instructions (object vs. image recognition). Old-new recognition performance for basic and subordinate level objects was measured in separate blocks. We found that for object recognition, view generalization between canonical and non-canonical views was comparable for basic level objects. For subordinate level objects, recognition performance was more accurate from non-canonical to canonical views than the other way around. When the task was changed from object recognition to image recognition, the pattern of the results reversed. Interestingly, participants responded “old” to “new” images of “old” objects with a substantially higher rate than to “new” objects, despite instructions to the contrary, thereby indicating involuntary view generalization. Our empirical findings are incompatible with the prediction of the view-approximation theory, and argue against the hypothesis that views are stored independently. PMID:23283692

Stereo Viewing Modulates Three-Dimensional Shape Processing During Object Recognition: A High-Density ERP Study

PubMed Central

2017-01-01

The role of stereo disparity in the recognition of 3-dimensional (3D) object shape remains an unresolved issue for theoretical models of the human visual system. We examined this issue using high-density (128 channel) recordings of event-related potentials (ERPs). A recognition memory task was used in which observers were trained to recognize a subset of complex, multipart, 3D novel objects under conditions of either (bi-) monocular or stereo viewing. In a subsequent test phase they discriminated previously trained targets from untrained distractor objects that shared either local parts, 3D spatial configuration, or neither dimension, across both previously seen and novel viewpoints. The behavioral data showed a stereo advantage for target recognition at untrained viewpoints. ERPs showed early differential amplitude modulations to shape similarity defined by local part structure and global 3D spatial configuration. This occurred initially during an N1 component around 145–190 ms poststimulus onset, and then subsequently during an N2/P3 component around 260–385 ms poststimulus onset. For mono viewing, amplitude modulation during the N1 was greatest between targets and distracters with different local parts for trained views only. For stereo viewing, amplitude modulation during the N2/P3 was greatest between targets and distracters with different global 3D spatial configurations and generalized across trained and untrained views. The results show that image classification is modulated by stereo information about the local part, and global 3D spatial configuration of object shape. The findings challenge current theoretical models that do not attribute functional significance to stereo input during the computation of 3D object shape. PMID:29022728

Acoustic interference and recognition space within a complex assemblage of dendrobatid frogs

PubMed Central

Amézquita, Adolfo; Flechas, Sandra Victoria; Lima, Albertina Pimentel; Gasser, Herbert; Hödl, Walter

2011-01-01

In species-rich assemblages of acoustically communicating animals, heterospecific sounds may constrain not only the evolution of signal traits but also the much less-studied signal-processing mechanisms that define the recognition space of a signal. To test the hypothesis that the recognition space is optimally designed, i.e., that it is narrower toward the species that represent the higher potential for acoustic interference, we studied an acoustic assemblage of 10 diurnally active frog species. We characterized their calls, estimated pairwise correlations in calling activity, and, to model the recognition spaces of five species, conducted playback experiments with 577 synthetic signals on 531 males. Acoustic co-occurrence was not related to multivariate distance in call parameters, suggesting a minor role for spectral or temporal segregation among species uttering similar calls. In most cases, the recognition space overlapped but was greater than the signal space, indicating that signal-processing traits do not act as strictly matched filters against sounds other than homospecific calls. Indeed, the range of the recognition space was strongly predicted by the acoustic distance to neighboring species in the signal space. Thus, our data provide compelling evidence of a role of heterospecific calls in evolutionarily shaping the frogs' recognition space within a complex acoustic assemblage without obvious concomitant effects on the signal. PMID:21969562

Speech Recognition in Adults With Cochlear Implants: The Effects of Working Memory, Phonological Sensitivity, and Aging.

PubMed

Moberly, Aaron C; Harris, Michael S; Boyce, Lauren; Nittrouer, Susan

2017-04-14

Models of speech recognition suggest that "top-down" linguistic and cognitive functions, such as use of phonotactic constraints and working memory, facilitate recognition under conditions of degradation, such as in noise. The question addressed in this study was what happens to these functions when a listener who has experienced years of hearing loss obtains a cochlear implant. Thirty adults with cochlear implants and 30 age-matched controls with age-normal hearing underwent testing of verbal working memory using digit span and serial recall of words. Phonological capacities were assessed using a lexical decision task and nonword repetition. Recognition of words in sentences in speech-shaped noise was measured. Implant users had only slightly poorer working memory accuracy than did controls and only on serial recall of words; however, phonological sensitivity was highly impaired. Working memory did not facilitate speech recognition in noise for either group. Phonological sensitivity predicted sentence recognition for implant users but not for listeners with normal hearing. Clinical speech recognition outcomes for adult implant users relate to the ability of these users to process phonological information. Results suggest that phonological capacities may serve as potential clinical targets through rehabilitative training. Such novel interventions may be particularly helpful for older adult implant users.

Speech Recognition in Adults With Cochlear Implants: The Effects of Working Memory, Phonological Sensitivity, and Aging

PubMed Central

Harris, Michael S.; Boyce, Lauren; Nittrouer, Susan

2017-01-01

Purpose Models of speech recognition suggest that “top-down” linguistic and cognitive functions, such as use of phonotactic constraints and working memory, facilitate recognition under conditions of degradation, such as in noise. The question addressed in this study was what happens to these functions when a listener who has experienced years of hearing loss obtains a cochlear implant. Method Thirty adults with cochlear implants and 30 age-matched controls with age-normal hearing underwent testing of verbal working memory using digit span and serial recall of words. Phonological capacities were assessed using a lexical decision task and nonword repetition. Recognition of words in sentences in speech-shaped noise was measured. Results Implant users had only slightly poorer working memory accuracy than did controls and only on serial recall of words; however, phonological sensitivity was highly impaired. Working memory did not facilitate speech recognition in noise for either group. Phonological sensitivity predicted sentence recognition for implant users but not for listeners with normal hearing. Conclusion Clinical speech recognition outcomes for adult implant users relate to the ability of these users to process phonological information. Results suggest that phonological capacities may serve as potential clinical targets through rehabilitative training. Such novel interventions may be particularly helpful for older adult implant users. PMID:28384805

Atypical development of configural face recognition in children with autism, Down syndrome and Williams syndrome.

PubMed

Dimitriou, D; Leonard, H C; Karmiloff-Smith, A; Johnson, M H; Thomas, M S C

2015-05-01

Configural processing in face recognition is a sensitivity to the spacing between facial features. It has been argued both that its presence represents a high level of expertise in face recognition, and also that it is a developmentally vulnerable process. We report a cross-syndrome investigation of the development of configural face recognition in school-aged children with autism, Down syndrome and Williams syndrome compared with a typically developing comparison group. Cross-sectional trajectory analyses were used to compare configural and featural face recognition utilising the 'Jane faces' task. Trajectories were constructed linking featural and configural performance either to chronological age or to different measures of mental age (receptive vocabulary, visuospatial construction), as well as the Benton face recognition task. An emergent inversion effect across age for detecting configural but not featural changes in faces was established as the marker of typical development. Children from clinical groups displayed atypical profiles that differed across all groups. We discuss the implications for the nature of face processing within the respective developmental disorders, and how the cross-sectional syndrome comparison informs the constraints that shape the typical development of face recognition. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

The Other-Race Effect Develops During Infancy

PubMed Central

Quinn, Paul C.; Slater, Alan M.; Lee, Kang; Ge, Liezhong; Pascalis, Olivier

2008-01-01

Experience plays a crucial role in the development of face processing. In the study reported here, we investigated how faces observed within the visual environment affect the development of the face-processing system during the 1st year of life. We assessed 3-, 6-, and 9-month-old Caucasian infants' ability to discriminate faces within their own racial group and within three other-race groups (African, Middle Eastern, and Chinese). The 3-month-old infants demonstrated recognition in all conditions, the 6-month-old infants were able to recognize Caucasian and Chinese faces only, and the 9-month-old infants' recognition was restricted to own-race faces. The pattern of preferences indicates that the other-race effect is emerging by 6 months of age and is present at 9 months of age. The findings suggest that facial input from the infant's visual environment is crucial for shaping the face-processing system early in infancy, resulting in differential recognition accuracy for faces of different races in adulthood. PMID:18031416

Bidirectional communication between amygdala and fusiform gyrus during facial recognition.

PubMed

Herrington, John D; Taylor, James M; Grupe, Daniel W; Curby, Kim M; Schultz, Robert T

2011-06-15

Decades of research have documented the specialization of fusiform gyrus (FG) for facial information processes. Recent theories indicate that FG activity is shaped by input from amygdala, but effective connectivity from amygdala to FG remains undocumented. In this fMRI study, 39 participants completed a face recognition task. 11 participants underwent the same experiment approximately four months later. Robust face-selective activation of FG, amygdala, and lateral occipital cortex were observed. Dynamic causal modeling and Bayesian Model Selection (BMS) were used to test the intrinsic connections between these structures, and their modulation by face perception. BMS results strongly favored a dynamic causal model with bidirectional, face-modulated amygdala-FG connections. However, the right hemisphere connections diminished at time 2, with the face modulation parameter no longer surviving Bonferroni correction. These findings suggest that amygdala strongly influences FG function during face perception, and that this influence is shaped by experience and stimulus salience. Copyright © 2011 Elsevier Inc. All rights reserved.

Research of Daily Conversation Transmitting System Based on Mouth Part Pattern Recognition

NASA Astrophysics Data System (ADS)

Watanabe, Mutsumi; Nishi, Natsuko

The authors are developing a vision-based intension transfer technique by recognizing user’s face expressions and movements, to help free and convenient communications with aged or disabled persons who find difficulties in talking, discriminating small character prints and operating keyboards by hands and fingers. In this paper we report a prototype system, where layered daily conversations are successively selected by recognizing the transition in shape of user’s mouth parts using camera image sequences settled in front of the user. Four mouth part patterns are used in the system. A method that automatically recognizes these patterns by analyzing the intensity histogram data around the mouth region is newly developed. The confirmation of a selection on the way is executed by detecting the open and shut movements of mouth through the temporal change in intensity histogram data. The method has been installed in a desktop PC by VC++ programs. Experimental results of mouth shape pattern recognition by twenty-five persons have shown the effectiveness of the method.

Combining point context and dynamic time warping for online gesture recognition

NASA Astrophysics Data System (ADS)

Mao, Xia; Li, Chen

2017-05-01

Previous gesture recognition methods usually focused on recognizing gestures after the entire gesture sequences were obtained. However, in many practical applications, a system has to identify gestures before they end to give instant feedback. We present an online gesture recognition approach that can realize early recognition of unfinished gestures with low latency. First, a curvature buffer-based point context (CBPC) descriptor is proposed to extract the shape feature of a gesture trajectory. The CBPC descriptor is a complete descriptor with a simple computation, and thus has its superiority in online scenarios. Then, we introduce an online windowed dynamic time warping algorithm to realize online matching between the ongoing gesture and the template gestures. In the algorithm, computational complexity is effectively decreased by adding a sliding window to the accumulative distance matrix. Lastly, the experiments are conducted on the Australian sign language data set and the Kinect hand gesture (KHG) data set. Results show that the proposed method outperforms other state-of-the-art methods especially when gesture information is incomplete.

Presentations of Shape in Object Recognition and Long-Term Visual Memory

DTIC Science & Technology

1994-04-05

theory of human image understanding . Psychological Review, 94, 115-147. Biederman, I., & Gerhardstein, P. C. (1993). Recognizing depth-rotated...Kybemetik. Submitted to Journal of Experimental Psychology: Human Perception and Performance. REFERENCES Biederman, I. (1987). Recognition-by-components: A

Congruent bodily arousal promotes the constructive recognition of emotional words.

PubMed

Kever, Anne; Grynberg, Delphine; Vermeulen, Nicolas

2017-08-01

Considerable research has shown that bodily states shape affect and cognition. Here, we examined whether transient states of bodily arousal influence the categorization speed of high arousal, low arousal, and neutral words. Participants realized two blocks of a constructive recognition task, once after a cycling session (increased arousal), and once after a relaxation session (reduced arousal). Results revealed overall faster response times for high arousal compared to low arousal words, and for positive compared to negative words. Importantly, low arousal words were categorized significantly faster after the relaxation than after the cycling, suggesting that a decrease in bodily arousal promotes the recognition of stimuli matching one's current arousal state. These findings highlight the importance of the arousal dimension in emotional processing, and suggest the presence of arousal-congruency effects. Copyright © 2017 Elsevier Inc. All rights reserved.

Recognition of rotated images using the multi-valued neuron and rotation-invariant 2D Fourier descriptors

NASA Astrophysics Data System (ADS)

Aizenberg, Evgeni; Bigio, Irving J.; Rodriguez-Diaz, Eladio

2012-03-01

The Fourier descriptors paradigm is a well-established approach for affine-invariant characterization of shape contours. In the work presented here, we extend this method to images, and obtain a 2D Fourier representation that is invariant to image rotation. The proposed technique retains phase uniqueness, and therefore structural image information is not lost. Rotation-invariant phase coefficients were used to train a single multi-valued neuron (MVN) to recognize satellite and human face images rotated by a wide range of angles. Experiments yielded 100% and 96.43% classification rate for each data set, respectively. Recognition performance was additionally evaluated under effects of lossy JPEG compression and additive Gaussian noise. Preliminary results show that the derived rotation-invariant features combined with the MVN provide a promising scheme for efficient recognition of rotated images.

Fragility of haptic memory in human full-term newborns.

PubMed

Lejeune, Fleur; Borradori Tolsa, Cristina; Gentaz, Edouard; Barisnikov, Koviljka

2018-05-31

Numerous studies have established that newborns can memorize tactile information about the specific features of an object with their hands and detect differences with another object. However, the robustness of haptic memory abilities has already been examined in preterm newborns and in full-term infants, but not yet in full-term newborns. This research is aimed to better understand the robustness of haptic memory abilities at birth by examining the effects of a change in the objects' temperature and haptic interference. Sixty-eight full-term newborns (mean postnatal age: 2.5 days) were included. The two experiments were conducted in three phases: habituation (repeated presentation of the same object, a prism or cylinder in the newborn's hand), discrimination (presentation of a novel object), and recognition (presentation of the familiar object). In Experiment 1, the change in the objects' temperature was controlled during the three phases. Results reveal that newborns can memorize specific features that differentiate prism and cylinder shapes by touch, and discriminate between them, but surprisingly they did not show evidence of recognizing them after interference. As no significant effect of the temperature condition was observed in habituation, discrimination and recognition abilities, these findings suggest that discrimination abilities in newborns may be determined by the detection of shape differences. Overall, it seems that the ontogenesis of haptic recognition memory is not linear. The developmental schedule is likely crucial for haptic development between 34 and 40 GW. Copyright © 2018 Elsevier Inc. All rights reserved.

Universal brain systems for recognizing word shapes and handwriting gestures during reading

PubMed Central

Nakamura, Kimihiro; Kuo, Wen-Jui; Pegado, Felipe; Cohen, Laurent; Tzeng, Ovid J. L.; Dehaene, Stanislas

2012-01-01

Do the neural circuits for reading vary across culture? Reading of visually complex writing systems such as Chinese has been proposed to rely on areas outside the classical left-hemisphere network for alphabetic reading. Here, however, we show that, once potential confounds in cross-cultural comparisons are controlled for by presenting handwritten stimuli to both Chinese and French readers, the underlying network for visual word recognition may be more universal than previously suspected. Using functional magnetic resonance imaging in a semantic task with words written in cursive font, we demonstrate that two universal circuits, a shape recognition system (reading by eye) and a gesture recognition system (reading by hand), are similarly activated and show identical patterns of activation and repetition priming in the two language groups. These activations cover most of the brain regions previously associated with culture-specific tuning. Our results point to an extended reading network that invariably comprises the occipitotemporal visual word-form system, which is sensitive to well-formed static letter strings, and a distinct left premotor region, Exner’s area, which is sensitive to the forward or backward direction with which cursive letters are dynamically presented. These findings suggest that cultural effects in reading merely modulate a fixed set of invariant macroscopic brain circuits, depending on surface features of orthographies. PMID:23184998

Glucocorticoid effects on object recognition memory require training-associated emotional arousal.

PubMed

Okuda, Shoki; Roozendaal, Benno; McGaugh, James L

2004-01-20

Considerable evidence implicates glucocorticoid hormones in the regulation of memory consolidation and memory retrieval. The present experiments investigated whether the influence of these hormones on memory depends on the level of emotional arousal induced by the training experience. We investigated this issue in male Sprague-Dawley rats by examining the effects of immediate posttraining systemic injections of the glucocorticoid corticosterone on object recognition memory under two conditions that differed in their training-associated emotional arousal. In rats that were not previously habituated to the experimental context, corticosterone (0.3, 1.0, or 3.0 mg/kg, s.c.) administered immediately after a 3-min training trial enhanced 24-hr retention performance in an inverted-U shaped dose-response relationship. In contrast, corticosterone did not affect 24-hr retention of rats that received extensive prior habituation to the experimental context and, thus, had decreased novelty-induced emotional arousal during training. Additionally, immediate posttraining administration of corticosterone to nonhabituated rats, in doses that enhanced 24-hr retention, impaired object recognition performance at a 1-hr retention interval whereas corticosterone administered after training to well-habituated rats did not impair 1-hr retention. Thus, the present findings suggest that training-induced emotional arousal may be essential for glucocorticoid effects on object recognition memory.

Monkeys recall and reproduce simple shapes from memory.

PubMed

Basile, Benjamin M; Hampton, Robert R

2011-05-10

If you draw from memory a picture of the front of your childhood home, you will have demonstrated recall. You could also recognize this house upon seeing it. Unlike recognition, recall demonstrates memory for things that are not present. Recall is necessary for planning and imagining, and it can increase the flexibility of navigation, social behavior, and other cognitive skills. Without recall, memory is more limited to recognition of the immediate environment. Amnesic patients are impaired on recall tests [1, 2], and recall performance often declines with aging [3]. Despite its importance, we know relatively little about nonhuman animals' ability to recall information; we lack suitable recall tests for them and depend instead on recognition tests to measure nonhuman memory. Here we report that rhesus monkeys can recall simple shapes from memory and reproduce them on a touchscreen. As in humans [4, 5], monkeys remembered less in recall than recognition tests, and their recall performance deteriorated more slowly. Transfer tests showed that monkeys used a flexible memory mechanism rather than memorizing specific actions for each shape. Observation of recall in Old World monkeys suggests that it has been adaptive for over 30 million years [6] and does not depend on language. Copyright © 2011 Elsevier Ltd. All rights reserved.

Shape Recognition in Infancy: Visual Integration of Sequential Information.

ERIC Educational Resources Information Center

Rose, Susan A

1988-01-01

Investigated infants' integration of visual information across space and time. In four experiments, infants aged 12 months and 6 months viewed objects after watching light trace similar and dissimilar shapes. Infants looked longer at novel shapes, although six-month-olds did not recognize figures taking more than 10 seconds to trace. One-year-old…

Shape Shifting: Local Landmarks Interfere with Navigation By, and Recognition Of, Global Shape

ERIC Educational Resources Information Center

Buckley, Matthew G.; Smith, Alastair D.; Haselgrove, Mark

2014-01-01

An influential theory of spatial navigation states that the boundary shape of an environment is preferentially encoded over and above other spatial cues, such that it is impervious to interference from alternative sources of information. We explored this claim with 3 intradimensional--extradimensional shift experiments, designed to examine the…

Shaping memory accuracy by left prefrontal transcranial direct current stimulation.

PubMed

Zwissler, Bastian; Sperber, Christoph; Aigeldinger, Sina; Schindler, Sebastian; Kissler, Johanna; Plewnia, Christian

2014-03-12

Human memory is dynamic and flexible but is also susceptible to distortions arising from adaptive as well as pathological processes. Both accurate and false memory formation require executive control that is critically mediated by the left prefrontal cortex (PFC). Transcranial direct current stimulation (tDCS) enables noninvasive modulation of cortical activity and associated behavior. The present study reports that tDCS applied to the left dorsolateral PFC (dlPFC) shaped accuracy of episodic memory via polaritiy-specific modulation of false recognition. When applied during encoding of pictures, anodal tDCS increased whereas cathodal stimulation reduced the number of false alarms to lure pictures in subsequent recognition memory testing. These data suggest that the enhancement of excitability in the dlPFC by anodal tDCS can be associated with blurred detail memory. In contrast, activity-reducing cathodal tDCS apparently acted as a noise filter inhibiting the development of imprecise memory traces and reducing the false memory rate. Consistently, the largest effect was found in the most active condition (i.e., for stimuli cued to be remembered). This first evidence for a polarity-specific, activity-dependent effect of tDCS on false memory opens new vistas for the understanding and potential treatment of disturbed memory control.

Case study of 3D fingerprints applications

PubMed Central

Liu, Feng; Liang, Jinrong; Shen, Linlin; Yang, Meng; Zhang, David; Lai, Zhihui

2017-01-01

Human fingers are 3D objects. More information will be provided if three dimensional (3D) fingerprints are available compared with two dimensional (2D) fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER) of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition. PMID:28399141

Case study of 3D fingerprints applications.

PubMed

Liu, Feng; Liang, Jinrong; Shen, Linlin; Yang, Meng; Zhang, David; Lai, Zhihui

2017-01-01

Human fingers are 3D objects. More information will be provided if three dimensional (3D) fingerprints are available compared with two dimensional (2D) fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER) of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition.

Enhanced associative memory for colour (but not shape or location) in synaesthesia.

PubMed

Pritchard, Jamie; Rothen, Nicolas; Coolbear, Daniel; Ward, Jamie

2013-05-01

People with grapheme-colour synaesthesia have been shown to have enhanced memory on a range of tasks using both stimuli that induce synaesthesia (e.g. words) and, more surprisingly, stimuli that do not (e.g. certain abstract visual stimuli). This study examines the latter by using multi-featured stimuli consisting of shape, colour and location conjunctions (e.g. shape A+colour A+location A; shape B+colour B+location B) presented in a recognition memory paradigm. This enables distractor items to be created in which one of these features is 'unbound' with respect to the others (e.g. shape A+colour B+location A; shape A+colour A+location C). Synaesthetes had higher recognition rates suggesting an enhanced ability to bind certain visual features together into memory. Importantly, synaesthetes' false alarm rates were lower only when colour was the unbound feature, not shape or location. We suggest that synaesthetes are "colour experts" and that enhanced perception can lead to enhanced memory in very specific ways; but, not for instance, an enhanced ability to form associations per se. The results support contemporary models that propose a continuum between perception and memory. Copyright © 2013 Elsevier B.V. All rights reserved.

Selective involvement of superior frontal cortex during working memory for shapes.

PubMed

Yee, Lydia T S; Roe, Katherine; Courtney, Susan M

2010-01-01

A spatial/nonspatial functional dissociation between the dorsal and ventral visual pathways is well established and has formed the basis of domain-specific theories of prefrontal cortex (PFC). Inconsistencies in the literature regarding prefrontal organization, however, have led to questions regarding whether the nature of the dissociations observed in PFC during working memory are equivalent to those observed in the visual pathways for perception. In particular, the dissociation between dorsal and ventral PFC during working memory for locations versus object identities has been clearly present in some studies but not in others, seemingly in part due to the type of objects used. The current study compared functional MRI activation during delayed-recognition tasks for shape or color, two object features considered to be processed by the ventral pathway for perceptual recognition. Activation for the shape-delayed recognition task was greater than that for the color task in the lateral occipital cortex, in agreement with studies of visual perception. Greater memory-delay activity was also observed, however, in the parietal and superior frontal cortices for the shape than for the color task. Activity in superior frontal cortex was associated with better performance on the shape task. Conversely, greater delay activity for color than for shape was observed in the left anterior insula and this activity was associated with better performance on the color task. These results suggest that superior frontal cortex contributes to performance on tasks requiring working memory for object identities, but it represents different information about those objects than does the ventral frontal cortex.

Aesthetic preference recognition of 3D shapes using EEG.

PubMed

Chew, Lin Hou; Teo, Jason; Mountstephens, James

2016-04-01

Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of physiological parameters. Numerous studies have been done to understand the relationship between human, art and aesthetics. In this paper, we present a novel preference-based measurement of user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes with motion. The 3D shapes are designed to appear like bracelets, which is generated by using the Gielis superformula. EEG signals were collected by using a medical grade device, the B-Alert X10 from advance brain monitoring, with a sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and delta rhythm by using time-frequency analysis, then classified into two classes, namely like and dislike by using support vector machines and K-nearest neighbors (KNN) classifiers respectively. Classification accuracy of up to 80 % was obtained by using KNN with the alpha, theta and delta rhythms as the features extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and dislike.

The perception of 3-D shape from shadows cast onto curved surfaces.

PubMed

Norman, J Farley; Lee, Young-lim; Phillips, Flip; Norman, Hideko F; Jennings, L RaShae; McBride, T Ryan

2009-05-01

In a natural environment, cast shadows abound. Objects cast shadows both upon themselves and upon background surfaces. Previous research on the perception of 3-D shape from cast shadows has only examined the informativeness of shadows cast upon flat background surfaces. In outdoor environments, however, background surfaces often possess significant curvature (large rocks, trees, hills, etc.), and this background curvature distorts the shape of cast shadows. The purpose of this study was to determine the extent to which observers can "discount" the distorting effects of curved background surfaces. In our experiments, observers viewed deforming or static shadows of naturally shaped objects, which were cast upon flat and curved background surfaces. The results showed that the discrimination of 3-D object shape from cast shadows was generally invariant over the distortions produced by hemispherical background surfaces. The observers often had difficulty, however, in identifying the shadows cast onto saddle-shaped background surfaces. The variations in curvature which occur in different directions on saddle-shaped background surfaces cause shadow distortions that lead to difficulties in object recognition and discrimination.

A Study Regarding the Spontaneous Use of Geometric Shapes in Young Children's Drawings

ERIC Educational Resources Information Center

Villarroel, José Domingo; Sanz Ortega, Olga

2017-01-01

The studies regarding how the comprehension of geometric shapes evolves in childhood are largely based on the assessment of children's responses during the course of tasks linked to the recognition, classification or explanation of prototypes and models. Little attention has been granted to the issue as to what extent the geometric shape turns out…

Prediction of the thermal imaging minimum resolvable (circle) temperature difference with neural network application.

PubMed

Fang, Yi-Chin; Wu, Bo-Wen

2008-12-01

Thermal imaging is an important technology in both national defense and the private sector. An advantage of thermal imaging is its ability to be deployed while fully engaged in duties, not limited by weather or the brightness of indoor or outdoor conditions. However, in an outdoor environment, many factors, including atmospheric decay, target shape, great distance, fog, temperature out of range and diffraction limits can lead to bad image formation, which directly affects the accuracy of object recognition. The visual characteristics of the human eye mean that it has a much better capacity for picture recognition under normal conditions than artificial intelligence does. However, conditions of interference significantly reduce this capacity for picture recognition for instance, fatigue impairs human eyesight. Hence, psychological and physiological factors can affect the result when the human eye is adopted to measure MRTD (minimum resolvable temperature difference) and MRCTD (minimum resolvable circle temperature difference). This study explores thermal imaging recognition, and presents a method for effectively choosing the characteristic values and processing the images fully. Neural network technology is successfully applied to recognize thermal imaging and predict MRTD and MRCTD (Appendix A), exceeding thermal imaging recognition under fatigue and the limits of the human eye.

Application of syntactic methods of pattern recognition for data mining and knowledge discovery in medicine

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Tadeusiewicz, Ryszard

2000-04-01

This paper presents and discusses possibilities of application of selected algorithms belonging to the group of syntactic methods of patten recognition used to analyze and extract features of shapes and to diagnose morphological lesions seen on selected medical images. This method is particularly useful for specialist morphological analysis of shapes of selected organs of abdominal cavity conducted to diagnose disease symptoms occurring in the main pancreatic ducts, upper segments of ureters and renal pelvis. Analysis of the correct morphology of these organs is possible with the application of the sequential and tree method belonging to the group of syntactic methods of pattern recognition. The objective of this analysis is to support early diagnosis of disease lesions, mainly characteristic for carcinoma and pancreatitis, based on examinations of ERCP images and a diagnosis of morphological lesions in ureters as well as renal pelvis based on an analysis of urograms. In the analysis of ERCP images the main objective is to recognize morphological lesions in pancreas ducts characteristic for carcinoma and chronic pancreatitis, while in the case of kidney radiogram analysis the aim is to diagnose local irregularities of ureter lumen and to examine the morphology of renal pelvis and renal calyxes. Diagnosing the above mentioned lesion has been conducted with the use of syntactic methods of pattern recognition, in particular the languages of description of features of shapes and context-free sequential attributed grammars. These methods allow to recognize and describe in a very efficient way the aforementioned lesions on images obtained as a result of initial image processing of width diagrams of the examined structures. Additionally, in order to support the analysis of the correct structure of renal pelvis a method using the tree grammar for syntactic pattern recognition to define its correct morphological shapes has been presented.

Recognition memory across the lifespan: the impact of word frequency and study-test interval on estimates of familiarity and recollection

PubMed Central

Meier, Beat; Rey-Mermet, Alodie; Rothen, Nicolas; Graf, Peter

2013-01-01

The goal of this study was to investigate recognition memory performance across the lifespan and to determine how estimates of recollection and familiarity contribute to performance. In each of three experiments, participants from five groups from 14 up to 85 years of age (children, young adults, middle-aged adults, young-old adults, and old-old adults) were presented with high- and low-frequency words in a study phase and were tested immediately afterwards and/or after a one day retention interval. The results showed that word frequency and retention interval affected recognition memory performance as well as estimates of recollection and familiarity. Across the lifespan, the trajectory of recognition memory followed an inverse u-shape function that was neither affected by word frequency nor by retention interval. The trajectory of estimates of recollection also followed an inverse u-shape function, and was especially pronounced for low-frequency words. In contrast, estimates of familiarity did not differ across the lifespan. The results indicate that age differences in recognition memory are mainly due to differences in processes related to recollection while the contribution of familiarity-based processes seems to be age-invariant. PMID:24198796

Perception of biological motion from size-invariant body representations.

PubMed

Lappe, Markus; Wittinghofer, Karin; de Lussanet, Marc H E

2015-01-01

The visual recognition of action is one of the socially most important and computationally demanding capacities of the human visual system. It combines visual shape recognition with complex non-rigid motion perception. Action presented as a point-light animation is a striking visual experience for anyone who sees it for the first time. Information about the shape and posture of the human body is sparse in point-light animations, but it is essential for action recognition. In the posturo-temporal filter model of biological motion perception posture information is picked up by visual neurons tuned to the form of the human body before body motion is calculated. We tested whether point-light stimuli are processed through posture recognition of the human body form by using a typical feature of form recognition, namely size invariance. We constructed a point-light stimulus that can only be perceived through a size-invariant mechanism. This stimulus changes rapidly in size from one image to the next. It thus disrupts continuity of early visuo-spatial properties but maintains continuity of the body posture representation. Despite this massive manipulation at the visuo-spatial level, size-changing point-light figures are spontaneously recognized by naive observers, and support discrimination of human body motion.

A re-examination of the mere exposure effect: The influence of repeated exposure on recognition, familiarity, and liking.

PubMed

Montoya, R Matthew; Horton, Robert S; Vevea, Jack L; Citkowicz, Martyna; Lauber, Elissa A

2017-05-01

To evaluate the veracity of models of the mere exposure effect and to understand the processes that moderate the effect, we conducted a meta-analysis of the influence of repeated exposure on liking, familiarity, recognition, among other evaluations. We estimated parameters from 268 curve estimates drawn from 81 articles and revealed that the mere exposure effect was characterized by a positive slope and negative quadratic effect consistent with an inverted-U shaped curve. In fact, such curves were associated with (a) all visual, but not auditory stimuli; (b) exposure durations shorter than 10 s and longer than 1 min; (c) both homogeneous and heterogeneous presentation types; and (d) ratings that were taken after all stimuli were presented. We conclude that existing models for the mere exposure effect do not adequately account for the findings, and we provide a framework to help guide future research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe -decay searches

NASA Astrophysics Data System (ADS)

Caldwell, A.; Cossavella, F.; Majorovits, B.; Palioselitis, D.; Volynets, O.

2015-07-01

A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate variations of efficiencies as a function of used training set. It is verified that neural networks are well-suited to identify background pulses in true-coaxial high-purity germanium detectors. The systematic uncertainty on the signal recognition efficiency derived using signal-like evaluation samples from calibration measurements is estimated to be 5 %. This uncertainty is due to differences between signal and calibration samples.

Context and Spoken Word Recognition in a Novel Lexicon

ERIC Educational Resources Information Center

Revill, Kathleen Pirog; Tanenhaus, Michael K.; Aslin, Richard N.

2008-01-01

Three eye movement studies with novel lexicons investigated the role of semantic context in spoken word recognition, contrasting 3 models: restrictive access, access-selection, and continuous integration. Actions directed at novel shapes caused changes in motion (e.g., looming, spinning) or state (e.g., color, texture). Across the experiments,…

The Shape of Things to Come: Evaluating Word Frequency as a Continuous Variable in Recognition Memory

ERIC Educational Resources Information Center

Hemmer, Pernille; Criss, Amy H.

2013-01-01

The role of experience in memory, specifically the word frequency (WF) mirror effect showing higher hit rates and lower false alarm rates for low-frequency words, is one of the hallmarks of memory. However, this "regularity of memory" is limited because normative WF has been treated as discrete (low vs. high). We evaluate the extent to…

Strategies for the Interpretive Integration of Ground and Aerial Views in UGV Operations

DTIC Science & Technology

2006-11-01

conjoinment of the psychological processes and effects of perception, object recognition (i.e. Biederman & Gerhardstein, 1993), navigation (Wickens...rather simple geon structural descriptions (GSD, see Biederman & 4 Gerhardstein, 1993). A geon is a basic three dimensional solid shape, such as a...large and reliable sex difference. Behavioral Brain Research, 93, 185-190. Biederman , I., & Gerhardstein, C. (1993). Recognizing depth- rotated objects

Is it the shape of the cavity, or the shape of the water in the cavity?

NASA Astrophysics Data System (ADS)

Snyder, Phillip W.; Lockett, Matthew R.; Moustakas, Demetri T.; Whitesides, George M.

2014-04-01

Historical interpretations of the thermodynamics characterizing biomolecular recognition have marginalized the role of water. An important (even, perhaps, dominant) contribution to molecular recognition in water comes from the "hydrophobic effect," in which non-polar portions of a ligand interact preferentially with non-polar regions of a protein. Water surrounds the ligand, and water fills the binding pocket of the protein: when the protein-ligand complex forms, and hydrophobic surfaces of the binding pocket and the ligand approach one another, the molecules (and hydrogen-bonded networks of molecules) of water associated with both surfaces rearrange and, in part, entirely escape into the bulk solution. It is now clear that neither of the two most commonly cited rationalizations for the hydrophobic effect-an entropy-dominated hydrophobic effect, in which ordered waters at the surface of the ligand, and water at the surface of the protein, are released to the bulk upon binding, and a "lock-and-key" model, in which the surface of a ligand interacts directly with a surface of a protein having a complementary shape-can account for water-mediated interactions between the ligand and the protein, and neither is sufficient to account for the experimental observation of both entropy- andenthalpy-dominated hydrophobic effects. What is now clear is that there is no single hydrophobic effect, with a universally applicable, common, thermodynamic description: different processes (i.e., partitioning between phases of different hydrophobicity, aggregation in water, and binding) with different thermodynamics, depend on the molecular-level details of the structures of the molecules involved, and of the aggregates that form. A "water-centric" description of the hydrophobic effect in biomolecular recognition focuses on the structures of water surrounding the ligand, and of water filling the binding pocket of the protein, both before and after binding. This view attributes the hydrophobic effect to changes in the free energy of the networks of hydrogen bonds that are formed, broken, or re-arranged when two hydrophobic surfaces approach (but do not necessarily contact) one another. The details of the molecular topography (and the polar character) of the mole- cular surfaces play an important role in determining the structure of these networks of hydrogen-bonded waters, and in the thermodynamic description of the hydrophobic effect(s). Theorists have led the formulation of this "water-centric view", although experiments are now supplying support for it. It poses complex problems for would-be "designers" of protein-ligand interactions, and for so-called "rational drug design".

Sentence Recognition Prediction for Hearing-impaired Listeners in Stationary and Fluctuation Noise With FADE

PubMed Central

Schädler, Marc René; Warzybok, Anna; Meyer, Bernd T.; Brand, Thomas

2016-01-01

To characterize the individual patient’s hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The “typical” audiogram shapes from Bisgaard et al with or without a “typical” level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only. PMID:27604782

Quantum dot nanocrystals having guanosine imprinted nanoshell for DNA recognition.

PubMed

Diltemiz, Sibel Emir; Say, Ridvan; Büyüktiryaki, Sibel; Hür, Deniz; Denizli, Adil; Ersöz, Arzu

2008-05-30

Molecular imprinted polymers (MIPs) as a recognition element for sensors are increasingly of interest and MIP nanoparticles have started to appear in the literature. In this study, we have proposed a novel thiol ligand-capping method with polymerizable methacryloylamido-cysteine (MAC) attached to CdS quantum dots (QDs), reminiscent of a self-assembled monolayer and have reconstructed surface shell by synthetic host polymers based on molecular imprinting method for DNA recognition. In this method, methacryloylamidohistidine-platinium (MAH-Pt(II)) is used as a new metal-chelating monomer via metal coordination-chelation interactions and guanosine templates of DNA. Nanoshell sensors with guanosine templates give a cavity that is selective for guanosine and its analogues. The guanosine can simultaneously chelate to Pt(II) metal ion and fit into the shape-selective cavity. Thus, the interaction between Pt(II) ion and free coordination spheres has an effect on the binding ability of the CdS QD nanosensor. The binding affinity of the guanosine imprinted nanocrystals has investigated by using the Langmuir and Scatchard methods, and experiments have shown the shape-selective cavity formation with O6 and N7 of a guanosine nucleotide (K(a) = 4.841x10(6) mol L(-1)) and a free guanine base (K(a) = 0.894x10(6) mol L(-1)). Additionally, the guanosine template of the nanocrystals is more favored for single stranded DNA compared to double stranded DNA.

Discriminability effect on Garner interference: evidence from recognition of facial identity and expression

PubMed Central

Wang, Yamin; Fu, Xiaolan; Johnston, Robert A.; Yan, Zheng

2013-01-01

Using Garner’s speeded classification task existing studies demonstrated an asymmetric interference in the recognition of facial identity and facial expression. It seems that expression is hard to interfere with identity recognition. However, discriminability of identity and expression, a potential confounding variable, had not been carefully examined in existing studies. In current work, we manipulated discriminability of identity and expression by matching facial shape (long or round) in identity and matching mouth (opened or closed) in facial expression. Garner interference was found either from identity to expression (Experiment 1) or from expression to identity (Experiment 2). Interference was also found in both directions (Experiment 3) or in neither direction (Experiment 4). The results support that Garner interference tends to occur under condition of low discriminability of relevant dimension regardless of facial property. Our findings indicate that Garner interference is not necessarily related to interdependent processing in recognition of facial identity and expression. The findings also suggest that discriminability as a mediating factor should be carefully controlled in future research. PMID:24391609

Development of the other-race effect during infancy: evidence toward universality?

PubMed

Kelly, David J; Liu, Shaoying; Lee, Kang; Quinn, Paul C; Pascalis, Olivier; Slater, Alan M; Ge, Liezhong

2009-09-01

The other-race effect in face processing develops within the first year of life in Caucasian infants. It is currently unknown whether the developmental trajectory observed in Caucasian infants can be extended to other cultures. This is an important issue to investigate because recent findings from cross-cultural psychology have suggested that individuals from Eastern and Western backgrounds tend to perceive the world in fundamentally different ways. To this end, the current study investigated 3-, 6-, and 9-month-old Chinese infants' ability to discriminate faces within their own racial group and within two other racial groups (African and Caucasian). The 3-month-olds demonstrated recognition in all conditions, whereas the 6-month-olds recognized Chinese faces and displayed marginal recognition for Caucasian faces but did not recognize African faces. The 9-month-olds' recognition was limited to Chinese faces. This pattern of development is consistent with the perceptual narrowing hypothesis that our perceptual systems are shaped by experience to be optimally sensitive to stimuli most commonly encountered in one's unique cultural environment.

Wild life passer species recognition from a technical passage through data fusion of a wireless sensor network

NASA Astrophysics Data System (ADS)

Gazis, A.; Katsiri, E.

2017-09-01

This paper presents a Wireless Sensor Network (WSN) system which was created as a project about protecting wildlife using sensor networks following the assistance of the department of Electrical and Computer Engineering of the Democritus University of Thrace. An automated process was implemented, regarding the recognition of a passenger (ie human, wolf, bear, etc.) traversing a box-shaped underground passage, such as the ones located along main highways fusing Width, Height and Weight values. These were measured using low-cost distance (beam) and weight (S-type load) micro-sensors and stored in a central repository. Moreover, the information provided by the WSN was analyzed, via a variety of methods including a neural pattern recognition network as well as clustering algorithms, which were able to recognize the kind of passenger, with certainty scores over 90%. The main concern, regarding the future, is the evaluation of these passages in respect to their effectiveness, i.e. whether they are frequently utilized by animals. This information was further analysed by appropriate information systems, in order to provide insights about the effectiveness of such mitigation structures.

Data encoding based on the shape of the ferroelectric domains produced by a scanning probe microscopy tip

DOE PAGES

Ievlev, Anton; Kalinin, Sergei V.

2015-05-28

Ferroelectric materials are broadly considered for information storage due to extremely high storage and information processing densities they enable. To date, ferroelectric based data storage has invariably relied on formation of cylindrical domains, allowing for binary information encoding. Here we demonstrate and explore the potential of high-density encoding based on domain morphology. We explore the domain morphogenesis during the tip-induced polarization switching by sequences of positive and negative pulses in a lithium niobate single-crystal and demonstrate the principal of information coding by shape and size of the domains. We applied cross-correlation and neural network approaches for recognition of the switchingmore » sequence by the shape of the resulting domains and establish optimal parameters for domain shape recognition. These studies both provide insight into the highly non-trivial mechanism of domain switching and potentially establish a new paradigm for multilevel information storage and content retrieval memories. Furthermore, this approach opens a pathway to exploration of domain switching mechanisms via shape analysis.« less

LGBT Family Lawyers and Same-Sex Marriage Recognition: How Legal Change Shapes Professional Identity and Practice.

PubMed

Baumle, Amanda K

2018-01-10

Lawyers who practice family law for LGBT clients are key players in the tenuous and evolving legal environment surrounding same-sex marriage recognition. Building on prior research on factors shaping the professional identities of lawyers generally, and activist lawyers specifically, I examine how practice within a rapidly changing, patchwork legal environment shapes professional identity for this group of lawyers. I draw on interviews with 21 LGBT family lawyers to analyze how the unique features of LGBT family law shape their professional identities and practice, as well as their predictions about the development of the practice in a post-Obergefell world. Findings reveal that the professional identities and practice of LGBT family lawyers are shaped by uncertainty, characteristics of activist lawyering, community membership, and community service. Individual motivations and institutional forces work to generate a professional identity that is resilient and dynamic, characterized by skepticism and distrust coupled with flexibility and creativity. These features are likely to play a role in the evolution of the LGBT family lawyer professional identity post-marriage equality.

Non-lambertian reflectance modeling and shape recovery of faces using tensor splines.

PubMed

Kumar, Ritwik; Barmpoutis, Angelos; Banerjee, Arunava; Vemuri, Baba C

2011-03-01

Modeling illumination effects and pose variations of a face is of fundamental importance in the field of facial image analysis. Most of the conventional techniques that simultaneously address both of these problems work with the Lambertian assumption and thus fall short of accurately capturing the complex intensity variation that the facial images exhibit or recovering their 3D shape in the presence of specularities and cast shadows. In this paper, we present a novel Tensor-Spline-based framework for facial image analysis. We show that, using this framework, the facial apparent BRDF field can be accurately estimated while seamlessly accounting for cast shadows and specularities. Further, using local neighborhood information, the same framework can be exploited to recover the 3D shape of the face (to handle pose variation). We quantitatively validate the accuracy of the Tensor Spline model using a more general model based on the mixture of single-lobed spherical functions. We demonstrate the effectiveness of our technique by presenting extensive experimental results for face relighting, 3D shape recovery, and face recognition using the Extended Yale B and CMU PIE benchmark data sets.

Multidimensional brain activity dictated by winner-take-all mechanisms.

PubMed

Tozzi, Arturo; Peters, James F

2018-06-21

A novel demon-based architecture is introduced to elucidate brain functions such as pattern recognition during human perception and mental interpretation of visual scenes. Starting from the topological concepts of invariance and persistence, we introduce a Selfridge pandemonium variant of brain activity that takes into account a novel feature, namely, demons that recognize short straight-line segments, curved lines and scene shapes, such as shape interior, density and texture. Low-level representations of objects can be mapped to higher-level views (our mental interpretations): a series of transformations can be gradually applied to a pattern in a visual scene, without affecting its invariant properties. This makes it possible to construct a symbolic multi-dimensional representation of the environment. These representations can be projected continuously to an object that we have seen and continue to see, thanks to the mapping from shapes in our memory to shapes in Euclidean space. Although perceived shapes are 3-dimensional (plus time), the evaluation of shape features (volume, color, contour, closeness, texture, and so on) leads to n-dimensional brain landscapes. Here we discuss the advantages of our parallel, hierarchical model in pattern recognition, computer vision and biological nervous system's evolution. Copyright © 2018 Elsevier B.V. All rights reserved.

Oriented active shape models.

PubMed

Liu, Jiamin; Udupa, Jayaram K

2009-04-01

Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks can be reduced by a factor of 3 in OASM over that in ASM; 3) OASM becomes largely independent of search range and initialization becomes automatic. All three benefits of OASM ensue mainly from the severe constraints brought in by the boundary-orientedness property of live wire and the globally optimal solution found by the 2-level dynamic programming algorithm.

Task effects, performance levels, features, configurations, and holistic face processing: A reply to Rossion

PubMed Central

Riesenhuber, Maximilian; Wolff, Brian S.

2009-01-01

Summary A recent article in Acta Psychologica (“Picture-plane inversion leads to qualitative changes of face perception” by B. Rossion, 2008) criticized several aspects of an earlier paper of ours (Riesenhuber et al., “Face processing in humans is compatible with a simple shape-based model of vision”, Proc Biol Sci, 2004). We here address Rossion’s criticisms and correct some misunderstandings. To frame the discussion, we first review our previously presented computational model of face recognition in cortex (Jiang et al., “Evaluation of a shape-based model of human face discrimination using fMRI and behavioral techniques”, Neuron, 2006) that provides a concrete biologically plausible computational substrate for holistic coding, namely a neural representation learned for upright faces, in the spirit of the original simple-to-complex hierarchical model of vision by Hubel and Wiesel. We show that Rossion’s and others’ data support the model, and that there is actually a convergence of views on the mechanisms underlying face recognition, in particular regarding holistic processing. PMID:19665104

Examination of the neighborhood activation theory in normal and hearing-impaired listeners.

PubMed

Dirks, D D; Takayanagi, S; Moshfegh, A; Noffsinger, P D; Fausti, S A

2001-02-01

Experiments were conducted to examine the effects of lexical information on word recognition among normal hearing listeners and individuals with sensorineural hearing loss. The lexical factors of interest were incorporated in the Neighborhood Activation Model (NAM). Central to this model is the concept that words are recognized relationally in the context of other phonemically similar words. NAM suggests that words in the mental lexicon are organized into similarity neighborhoods and the listener is required to select the target word from competing lexical items. Two structural characteristics of similarity neighborhoods that influence word recognition have been identified; "neighborhood density" or the number of phonemically similar words (neighbors) for a particular target item and "neighborhood frequency" or the average frequency of occurrence of all the items within a neighborhood. A third lexical factor, "word frequency" or the frequency of occurrence of a target word in the language, is assumed to optimize the word recognition process by biasing the system toward choosing a high frequency over a low frequency word. Three experiments were performed. In the initial experiments, word recognition for consonant-vowel-consonant (CVC) monosyllables was assessed in young normal hearing listeners by systematically partitioning the items into the eight possible lexical conditions that could be created by two levels of the three lexical factors, word frequency (high and low), neighborhood density (high and low), and average neighborhood frequency (high and low). Neighborhood structure and word frequency were estimated computationally using a large, on-line lexicon-based Webster's Pocket Dictionary. From this program 400 highly familiar, monosyllables were selected and partitioned into eight orthogonal lexical groups (50 words/group). The 400 words were presented randomly to normal hearing listeners in speech-shaped noise (Experiment 1) and "in quiet" (Experiment 2) as well as to an elderly group of listeners with sensorineural hearing loss in the speech-shaped noise (Experiment 3). The results of three experiments verified predictions of NAM in both normal hearing and hearing-impaired listeners. In each experiment, words from low density neighborhoods were recognized more accurately than those from high density neighborhoods. The presence of high frequency neighbors (average neighborhood frequency) produced poorer recognition performance than comparable conditions with low frequency neighbors. Word frequency was found to have a highly significant effect on word recognition. Lexical conditions with high word frequencies produced higher performance scores than conditions with low frequency words. The results supported the basic tenets of NAM theory and identified both neighborhood structural properties and word frequency as significant lexical factors affecting word recognition when listening in noise and "in quiet." The results of the third experiment permit extension of NAM theory to individuals with sensorineural hearing loss. Future development of speech recognition tests should allow for the effects of higher level cognitive (lexical) factors on lower level phonemic processing.

Acute effects of alcohol on intrusive memory development and viewpoint dependence in spatial memory support a dual representation model.

PubMed

Bisby, James A; King, John A; Brewin, Chris R; Burgess, Neil; Curran, H Valerie

2010-08-01

A dual representation model of intrusive memory proposes that personally experienced events give rise to two types of representation: an image-based, egocentric representation based on sensory-perceptual features; and a more abstract, allocentric representation that incorporates spatiotemporal context. The model proposes that intrusions reflect involuntary reactivation of egocentric representations in the absence of a corresponding allocentric representation. We tested the model by investigating the effect of alcohol on intrusive memories and, concurrently, on egocentric and allocentric spatial memory. With a double-blind independent group design participants were administered alcohol (.4 or .8 g/kg) or placebo. A virtual environment was used to present objects and test recognition memory from the same viewpoint as presentation (tapping egocentric memory) or a shifted viewpoint (tapping allocentric memory). Participants were also exposed to a trauma video and required to detail intrusive memories for 7 days, after which explicit memory was assessed. There was a selective impairment of shifted-view recognition after the low dose of alcohol, whereas the high dose induced a global impairment in same-view and shifted-view conditions. Alcohol showed a dose-dependent inverted "U"-shaped effect on intrusions, with only the low dose increasing the number of intrusions, replicating previous work. When same-view recognition was intact, decrements in shifted-view recognition were associated with increases in intrusions. The differential effect of alcohol on intrusive memories and on same/shifted-view recognition support a dual representation model in which intrusions might reflect an imbalance between two types of memory representation. These findings highlight important clinical implications, given alcohol's involvement in real-life trauma. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Monodispersed molecularly imprinted polymer for creatinine by modified precipitation polymerization.

PubMed

Haginaka, Jun; Miura, Chitose; Funaya, Noriko; Matsunaga, Hisami

2012-01-01

A monodispersed molecularly imprinted polymer (MIP) for creatinine was prepared by modified precipitation polymerization. The retention and molecular-recognition properties of the prepared MIP were evaluated by the hydrophilic interaction chromatography mode using a mixture of ammonium acetate buffer and acetonitrile as a mobile phase in liquid chromatography. The MIP had a specific recognition ability for creatinine, while other structurally related compounds, such as hydantoin, 1-methylhydantoin, 2-pyrrolidone, N-hydroxysuccinimide and creatine, could not be recognized on the MIP. In addition to shape recognition, hydrophilic interactions could work for the recognition of creatinine on the MIP.

Face Recognition Is Shaped by the Use of Sign Language

ERIC Educational Resources Information Center

Stoll, Chloé; Palluel-Germain, Richard; Caldara, Roberto; Lao, Junpeng; Dye, Matthew W. G.; Aptel, Florent; Pascalis, Olivier

2018-01-01

Previous research has suggested that early deaf signers differ in face processing. Which aspects of face processing are changed and the role that sign language may have played in that change are however unclear. Here, we compared face categorization (human/non-human) and human face recognition performance in early profoundly deaf signers, hearing…

Two-dimensional shape recognition using oriented-polar representation

NASA Astrophysics Data System (ADS)

Hu, Neng-Chung; Yu, Kuo-Kan; Hsu, Yung-Li

1997-10-01

To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant in spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.

Peptidoglycan microarray as a novel tool to explore protein-ligand recognition.

PubMed

Wang, Ning; Hirata, Akiyoshi; Nokihara, Kiyoshi; Fukase, Koichi; Fujimoto, Yukari

2016-11-04

Peptidoglycan is a giant bag-shaped molecule essential for bacterial cell shape and resistance to osmotic stresses. The activity of a large number of bacterial surface proteins involved in cell growth and division requires binding to this macromolecule. Recognition of peptidoglycan by immune effectors is also crucial for the establishment of the immune response against pathogens. The availability of pure and chemically defined peptidoglycan fragments is a major technical bottleneck that has precluded systematic studies of the mechanisms underpinning protein-mediated peptidoglycan recognition. Here, we report a microarray strategy suitable to carry out comprehensive studies to characterize proteins-peptidoglycan interactions. We describe a method to introduce a functional group on peptidoglycan fragments allowing their stable immobilization on amorphous carbon chip plates to minimize nonspecific binding. Such peptidoglycan microarrays were used with a model peptidoglycan binding protein-the human peptidoglycan recognition protein-S (hPGRP-S). We propose that this strategy could be implemented to carry out high-throughput analyses to study peptidoglycan binding proteins. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 422-429, 2016. © 2016 Wiley Periodicals, Inc.

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Dynamic representation of partially occluded objects in primate prefrontal and visual cortex

PubMed Central

Choi, Hannah; Shea-Brown, Eric

2017-01-01

Successful recognition of partially occluded objects is presumed to involve dynamic interactions between brain areas responsible for vision and cognition, but neurophysiological evidence for the involvement of feedback signals is lacking. Here, we demonstrate that neurons in the ventrolateral prefrontal cortex (vlPFC) of monkeys performing a shape discrimination task respond more strongly to occluded than unoccluded stimuli. In contrast, neurons in visual area V4 respond more strongly to unoccluded stimuli. Analyses of V4 response dynamics reveal that many neurons exhibit two transient response peaks, the second of which emerges after vlPFC response onset and displays stronger selectivity for occluded shapes. We replicate these findings using a model of V4/vlPFC interactions in which occlusion-sensitive vlPFC neurons feed back to shape-selective V4 neurons, thereby enhancing V4 responses and selectivity to occluded shapes. These results reveal how signals from frontal and visual cortex could interact to facilitate object recognition under occlusion. PMID:28925354

Deep neural network using color and synthesized three-dimensional shape for face recognition

NASA Astrophysics Data System (ADS)

Rhee, Seon-Min; Yoo, ByungIn; Han, Jae-Joon; Hwang, Wonjun

2017-03-01

We present an approach for face recognition using synthesized three-dimensional (3-D) shape information together with two-dimensional (2-D) color in a deep convolutional neural network (DCNN). As 3-D facial shape is hardly affected by the extrinsic 2-D texture changes caused by illumination, make-up, and occlusions, it could provide more reliable complementary features in harmony with the 2-D color feature in face recognition. Unlike other approaches that use 3-D shape information with the help of an additional depth sensor, our approach generates a personalized 3-D face model by using only face landmarks in the 2-D input image. Using the personalized 3-D face model, we generate a frontalized 2-D color facial image as well as 3-D facial images (e.g., a depth image and a normal image). In our DCNN, we first feed 2-D and 3-D facial images into independent convolutional layers, where the low-level kernels are successfully learned according to their own characteristics. Then, we merge them and feed into higher-level layers under a single deep neural network. Our proposed approach is evaluated with labeled faces in the wild dataset and the results show that the error rate of the verification rate at false acceptance rate 1% is improved by up to 32.1% compared with the baseline where only a 2-D color image is used.

3D palmprint data fast acquisition and recognition

NASA Astrophysics Data System (ADS)

Wang, Xiaoxu; Huang, Shujun; Gao, Nan; Zhang, Zonghua

2014-11-01

This paper presents a fast 3D (Three-Dimension) palmprint capturing system and develops an efficient 3D palmprint feature extraction and recognition method. In order to fast acquire accurate 3D shape and texture of palmprint, a DLP projector triggers a CCD camera to realize synchronization. By generating and projecting green fringe pattern images onto the measured palm surface, 3D palmprint data are calculated from the fringe pattern images. The periodic feature vector can be derived from the calculated 3D palmprint data, so undistorted 3D biometrics is obtained. Using the obtained 3D palmprint data, feature matching test have been carried out by Gabor filter, competition rules and the mean curvature. Experimental results on capturing 3D palmprint show that the proposed acquisition method can fast get 3D shape information of palmprint. Some initial experiments on recognition show the proposed method is efficient by using 3D palmprint data.

A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-Rigid Shape Matching

DTIC Science & Technology

2009-02-01

topology changes. We used a subset of the TOSCA shape database , [10], consisting of four different objects: cat, dog, male, and female. Each of the...often encountered as acquisition imperfections when the shapes are acquired using a 3D scanner. We used a subset of the TOSCA shape database , consisting...object recognition, Point Based Graphics, Prague, 2007. 18 44. A. Spira and R. Kimmel, An efficient solution to the eikonal equation on parametric

Frontal sinus recognition for human identification

NASA Astrophysics Data System (ADS)

Falguera, Juan Rogelio; Falguera, Fernanda Pereira Sartori; Marana, Aparecido Nilceu

2008-03-01

Many methods based on biometrics such as fingerprint, face, iris, and retina have been proposed for person identification. However, for deceased individuals, such biometric measurements are not available. In such cases, parts of the human skeleton can be used for identification, such as dental records, thorax, vertebrae, shoulder, and frontal sinus. It has been established in prior investigations that the radiographic pattern of frontal sinus is highly variable and unique for every individual. This has stimulated the proposition of measurements of the frontal sinus pattern, obtained from x-ray films, for skeletal identification. This paper presents a frontal sinus recognition method for human identification based on Image Foresting Transform and shape context. Experimental results (ERR = 5,82%) have shown the effectiveness of the proposed method.

Exploring Biomolecular Recognition by Modeling and Simulation

NASA Astrophysics Data System (ADS)

Wade, Rebecca

2007-12-01

Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

Variations in recollection: the effects of complexity on source recognition.

PubMed

Parks, Colleen M; Murray, Linda J; Elfman, Kane; Yonelinas, Andrew P

2011-07-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in favor of the threshold assumption, but zROCs are not always as U-shaped as threshold theory predicts. Source zROCs have been shown to become more linear when the contribution of familiarity to source discriminations is increased, and this may account for the existing results. However, another way in which source zROCs may become more linear is if the recollection threshold begins to break down and recollection becomes more graded and Gaussian. We tested the "graded recollection" account in the current study. We found that increasing stimulus complexity (i.e., changing from single words to sentences) or increasing source complexity (i.e., changing the sources from audio to videos of speakers) resulted in flatter source zROCs. In addition, conditions expected to reduce recollection (i.e., divided attention and amnesia) had comparable effects on source memory in simple and complex conditions, suggesting that differences between simple and complex conditions were due to differences in the nature of recollection, rather than differences in the utility of familiarity. The results suggest that under conditions of high complexity, recollection can appear more graded, and it can produce curved ROCs. The results have implications for measurement models and for current theories of recognition memory.

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors

PubMed Central

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-01-01

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing “Palm Downward” sign gestures from “Palm Inward” ones. Only the “Palm Inward” gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no training samples to model even though the same coded gesture performed in different characters. This work opens up a possible new way to realize a practical Chinese SLR system. PMID:26389907

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors.

PubMed

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-09-15

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing "Palm Downward" sign gestures from "Palm Inward" ones. Only the "Palm Inward" gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no training samples to model even though the same coded gesture performed in different characters. This work opens up a possible new way to realize a practical Chinese SLR system.

Evidence for two attentional components in visual working memory.

PubMed

Allen, Richard J; Baddeley, Alan D; Hitch, Graham J

2014-11-01

How does executive attentional control contribute to memory for sequences of visual objects, and what does this reveal about storage and processing in working memory? Three experiments examined the impact of a concurrent executive load (backward counting) on memory for sequences of individually presented visual objects. Experiments 1 and 2 found disruptive concurrent load effects of equivalent magnitude on memory for shapes, colors, and colored shape conjunctions (as measured by single-probe recognition). These effects were present only for Items 1 and 2 in a 3-item sequence; the final item was always impervious to this disruption. This pattern of findings was precisely replicated in Experiment 3 when using a cued verbal recall measure of shape-color binding, with error analysis providing additional insights concerning attention-related loss of early-sequence items. These findings indicate an important role for executive processes in maintaining representations of earlier encountered stimuli in an active form alongside privileged storage of the most recent stimulus. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Shapes displayed with durations in the microsecond range do not obey Bloch's law of temporal summation

PubMed Central

Greene, Ernest; Ogden, R. Todd

2013-01-01

Shape patterns were displayed with simultaneous brief flashes from a light-emitting diode array. Flash durations in the microsecond range and luminous intensities were adjusted to vary the degree of successful shape recognition. Four experiments were conducted to test whether Bloch's law would apply in this task. Bloch's law holds that for very brief flashes the perceptual threshold is determined by the total number of photons being delivered, i.e., there is reciprocity of intensity and duration. The present results did not find that effectiveness of flashes was based on the total quantity of photons, as predicted by Bloch's law. Additionally, the evidence points to a visual mechanism that has ultra-high temporal precision that either registers the rate of photon flux or the duration of flashes. PMID:24349700

Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

NASA Astrophysics Data System (ADS)

El-Saba, A. M.; Alam, M. S.; Surpanani, A.

2006-05-01

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

Evidence for the role of shape in mental representations of similes.

PubMed

van Weelden, Lisanne; Schilperoord, Joost; Maes, Alfons

2014-03-01

People mentally represent the shapes of objects. For instance, the mental representation of an eagle is different when one thinks about a flying or resting eagle. This study examined the role of shape in mental representations of similes (i.e., metaphoric comparisons). We tested the prediction that when people process a simile they will mentally represent the entities of the comparison as having a similar shape. We conducted two experiments in which participants read sentences that either did (experimental sentences) or did not (control sentences) invite comparing two entities. For the experimental sentences, the ground of the comparison was explicit in Experiment 1 ("X has the ability to Z, just like Y") and implicit in Experiment 2 ("X is like Y"). After having read the sentence, participants were presented with line drawings of the two objects, which were either similarly or dissimilarly shaped. They judged whether both objects were mentioned in the preceding sentence. For the experimental sentences, recognition latencies were shorter for similarly shaped objects than for dissimilarly shaped objects. For the control sentences, we did not find such an effect of similarity in shape. These findings suggest that a perceptual symbol of shape is activated when processing similes. © 2013 Cognitive Science Society, Inc.

Variety of geologic silhouette shapes distinguishable by multiple rotations method of quantitative shape analysis text

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, D.G.; Parks, J.M.

1984-04-01

Silhouette shapes are two-dimensional projections of three-dimensional objects such as sand grains, gravel, and fossils. Within-the-margin markings such as chamber boundaries, sutures, or ribs are ignored. Comparisons between populations of objects from similar and differential origins (i.e., environments, species or genera, growth series, etc) is aided by quantifying the shapes. The Multiple Rotations Method (MRM) uses a variation of ''eigenshapes'', which is capable of distinguishing most of the subtle variations that the ''trained eye'' can detect. With a video-digitizer and microcomputer, MRM is fast, more accurate, and more objective than the human eye. The resulting shape descriptors comprise 5 ormore » 6 numbers per object that can be stored and retrieved to compare with similar descriptions of other objects. The original-shape outlines can be reconstituted sufficiently for gross recognition from these few numerical descriptors. Thus, a semi-automated data-retrieval system becomes feasible, with silhouette-shape descriptions as one of several recognition criteria. MRM consists of four ''rotations'': rotation about a center to a comparable orientation; a principal-components rotation to reduce the many original shape descriptors to a few; a VARIMAX orthogonal-factor rotation to achieve simple structure; and a rotation to achieve factor scores on individual objects. A variety of subtly different shapes includes sand grains from several locations, ages, and environments, and fossils of several types. This variety illustrates the feasibility of quantitative comparisons by MRM.« less

Intrinsic and contextual features in object recognition.

PubMed

Schlangen, Derrick; Barenholtz, Elan

2015-01-28

The context in which an object is found can facilitate its recognition. Yet, it is not known how effective this contextual information is relative to the object's intrinsic visual features, such as color and shape. To address this, we performed four experiments using rendered scenes with novel objects. In each experiment, participants first performed a visual search task, searching for a uniquely shaped target object whose color and location within the scene was experimentally manipulated. We then tested participants' tendency to use their knowledge of the location and color information in an identification task when the objects' images were degraded due to blurring, thus eliminating the shape information. In Experiment 1, we found that, in the absence of any diagnostic intrinsic features, participants identified objects based purely on their locations within the scene. In Experiment 2, we found that participants combined an intrinsic feature, color, with contextual location in order to uniquely specify an object. In Experiment 3, we found that when an object's color and location information were in conflict, participants identified the object using both sources of information equally. Finally, in Experiment 4, we found that participants used whichever source of information-either color or location-was more statistically reliable in order to identify the target object. Overall, these experiments show that the context in which objects are found can play as important a role as intrinsic features in identifying the objects. © 2015 ARVO.

Sentence Recognition Prediction for Hearing-impaired Listeners in Stationary and Fluctuation Noise With FADE: Empowering the Attenuation and Distortion Concept by Plomp With a Quantitative Processing Model.

PubMed

Kollmeier, Birger; Schädler, Marc René; Warzybok, Anna; Meyer, Bernd T; Brand, Thomas

2016-09-07

To characterize the individual patient's hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The "typical" audiogram shapes from Bisgaard et al with or without a "typical" level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only. © The Author(s) 2016.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Shape-specific perceptual learning in a figure-ground segregation task.

PubMed

Yi, Do-Joon; Olson, Ingrid R; Chun, Marvin M

2006-03-01

What does perceptual experience contribute to figure-ground segregation? To study this question, we trained observers to search for symmetric dot patterns embedded in random dot backgrounds. Training improved shape segmentation, but learning did not completely transfer either to untrained locations or to untrained shapes. Such partial specificity persisted for a month after training. Interestingly, training on shapes in empty backgrounds did not help segmentation of the trained shapes in noisy backgrounds. Our results suggest that perceptual training increases the involvement of early sensory neurons in the segmentation of trained shapes, and that successful segmentation requires perceptual skills beyond shape recognition alone.

Support vector machine for automatic pain recognition

NASA Astrophysics Data System (ADS)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

Compact optical processor for Hough and frequency domain features

NASA Astrophysics Data System (ADS)

Ott, Peter

1996-11-01

Shape recognition is necessary in a broad band of applications such as traffic sign or work piece recognition. It requires not only neighborhood processing of the input image pixels but global interconnection of them. The Hough transform (HT) performs such a global operation and it is well suited in the preprocessing stage of a shape recognition system. Translation invariant features can be easily calculated form the Hough domain. We have implemented on the computer a neural network shape recognition system which contains a HT, a feature extraction, and a classification layer. The advantage of this approach is that the total system can be optimized with well-known learning techniques and that it can explore the parallelism of the algorithms. However, the HT is a time consuming operation. Parallel, optical processing is therefore advantageous. Several systems have been proposed, based on space multiplexing with arrays of holograms and CGH's or time multiplexing with acousto-optic processors or by image rotation with incoherent and coherent astigmatic optical processors. We took up the last mentioned approach because 2D array detectors are read out line by line, so a 2D detector can achieve the same speed and is easier to implement. Coherent processing can allow the implementation of tilers in the frequency domain. Features based on wedge/ring, Gabor, or wavelet filters have been proven to show good discrimination capabilities for texture and shape recognition. The astigmatic lens system which is derived form the mathematical formulation of the HT is long and contains a non-standard, astigmatic element. By methods of lens transformation s for coherent applications we map the original design to a shorter lens with a smaller number of well separated standard elements and with the same coherent system response. The final lens design still contains the frequency plane for filtering and ray-tracing shows diffraction limited performance. Image rotation can be done optically by a rotating prism. We realize it on a fast FLC- SLM of our lab as input device. The filters can be implemented on the same type of SLM with 128 by 128 square pixels of size, resulting in a total length of the lens of less than 50cm.

Shape, color, and the other-race effect in the infant brain

PubMed Central

Balas, Benjamin; Westerlund, Alissa; Hung, Katherine; Nelson, Charles A.

2015-01-01

The “other-race” effect describes the phenomenon in which faces are difficult to distinguish from one another if they belong to an ethnic or racial group to which the observer has had little exposure. Adult observers typically display multiple forms of recognition error for other-race faces, and infants exhibit behavioral evidence of a developing other-race effect at about 9 months of age. The neural correlates of the adult other-race effect have been identified using ERPs and fMRI, but the effects of racial category on infants’ neural response to face stimuli have to date not been described. We examine two distinct components of the infant ERP response to human faces and demonstrate through the use of computer-generated “hybrid” faces that the observed other-race effect is not the result of low-level sensitivity to 3D shape and color differences between the stimuli. Rather, differential processing depends critically on the joint encoding of race-specific features. PMID:21676108

Super Normal Vector for Human Activity Recognition with Depth Cameras.

PubMed

Yang, Xiaodong; Tian, YingLi

2017-05-01

The advent of cost-effectiveness and easy-operation depth cameras has facilitated a variety of visual recognition tasks including human activity recognition. This paper presents a novel framework for recognizing human activities from video sequences captured by depth cameras. We extend the surface normal to polynormal by assembling local neighboring hypersurface normals from a depth sequence to jointly characterize local motion and shape information. We then propose a general scheme of super normal vector (SNV) to aggregate the low-level polynormals into a discriminative representation, which can be viewed as a simplified version of the Fisher kernel representation. In order to globally capture the spatial layout and temporal order, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time cells. In the extensive experiments, the proposed approach achieves superior performance to the state-of-the-art methods on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.

Contributions of familiarity and recollection rejection to recognition: Evidence from the time course of false recognition for semantic and conjunction lures

PubMed Central

Matzen, Laura E.; Taylor, Eric G.; Benjamin, Aaron S.

2010-01-01

It has been suggested that both familiarity and recollection contribute to the recognition decision process. In this paper, we leverage the form of false alarm rate functions—in which false-alarm rates describe an inverted U-shaped function as the time between study and test increases—to assess how these processes support retention of semantic and surface form information from previously studied words. We directly compare the maxima of these functions for lures that are semantically related and lures that are related by surface form to previously studied material. This analysis reveals a more rapid loss of access to surface form than to semantic information. To separate the contributions of item familiarity and reminding-induced recollection rejection to this effect, we use a simple multinomial process model; this analysis reveals that this loss of access reflects both a more rapid loss of familiarity and lower rates of recollection for surface form information. PMID:21240745

Textual and shape-based feature extraction and neuro-fuzzy classifier for nuclear track recognition

NASA Astrophysics Data System (ADS)

Khayat, Omid; Afarideh, Hossein

2013-04-01

Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.

SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition.

PubMed

Wei, Ning-Ning; Hamza, Adel

2014-01-27

We present an efficient and rational ligand/structure shape-based virtual screening approach combining our previous ligand shape-based similarity SABRE (shape-approach-based routines enhanced) and the 3D shape of the receptor binding site. Our approach exploits the pharmacological preferences of a number of known active ligands to take advantage of the structural diversities and chemical similarities, using a linear combination of weighted molecular shape density. Furthermore, the algorithm generates a consensus molecular-shape pattern recognition that is used to filter and place the candidate structure into the binding pocket. The descriptor pool used to construct the consensus molecular-shape pattern consists of four dimensional (4D) fingerprints generated from the distribution of conformer states available to a molecule and the 3D shapes of a set of active ligands computed using SABRE software. The virtual screening efficiency of SABRE was validated using the Database of Useful Decoys (DUD) and the filtered version (WOMBAT) of 10 DUD targets. The ligand/structure shape-based similarity SABRE algorithm outperforms several other widely used virtual screening methods which uses the data fusion of multiscreening tools (2D and 3D fingerprints) and demonstrates a superior early retrieval rate of active compounds (EF(0.1%) = 69.0% and EF(1%) = 98.7%) from a large size of ligand database (∼95,000 structures). Therefore, our developed similarity approach can be of particular use for identifying active compounds that are similar to reference molecules and predicting activity against other targets (chemogenomics). An academic license of the SABRE program is available on request.

Speech recognition in one- and two-talker maskers in school-age children and adults: Development of perceptual masking and glimpsing

PubMed Central

Buss, Emily; Leibold, Lori J.; Porter, Heather L.; Grose, John H.

2017-01-01

Children perform more poorly than adults on a wide range of masked speech perception paradigms, but this effect is particularly pronounced when the masker itself is also composed of speech. The present study evaluated two factors that might contribute to this effect: the ability to perceptually isolate the target from masker speech, and the ability to recognize target speech based on sparse cues (glimpsing). Speech reception thresholds (SRTs) were estimated for closed-set, disyllabic word recognition in children (5–16 years) and adults in a one- or two-talker masker. Speech maskers were 60 dB sound pressure level (SPL), and they were either presented alone or in combination with a 50-dB-SPL speech-shaped noise masker. There was an age effect overall, but performance was adult-like at a younger age for the one-talker than the two-talker masker. Noise tended to elevate SRTs, particularly for older children and adults, and when summed with the one-talker masker. Removing time-frequency epochs associated with a poor target-to-masker ratio markedly improved SRTs, with larger effects for younger listeners; the age effect was not eliminated, however. Results were interpreted as indicating that development of speech-in-speech recognition is likely impacted by development of both perceptual masking and the ability recognize speech based on sparse cues. PMID:28464682

Performance of Language-Coordinated Collective Systems: A Study of Wine Recognition and Description

PubMed Central

Zubek, Julian; Denkiewicz, Michał; Dębska, Agnieszka; Radkowska, Alicja; Komorowska-Mach, Joanna; Litwin, Piotr; Stępień, Magdalena; Kucińska, Adrianna; Sitarska, Ewa; Komorowska, Krystyna; Fusaroli, Riccardo; Tylén, Kristian; Rączaszek-Leonardi, Joanna

2016-01-01

Most of our perceptions of and engagements with the world are shaped by our immersion in social interactions, cultural traditions, tools and linguistic categories. In this study we experimentally investigate the impact of two types of language-based coordination on the recognition and description of complex sensory stimuli: that of red wine. Participants were asked to taste, remember and successively recognize samples of wines within a larger set in a two-by-two experimental design: (1) either individually or in pairs, and (2) with or without the support of a sommelier card—a cultural linguistic tool designed for wine description. Both effectiveness of recognition and the kinds of errors in the four conditions were analyzed. While our experimental manipulations did not impact recognition accuracy, bias-variance decomposition of error revealed non-trivial differences in how participants solved the task. Pairs generally displayed reduced bias and increased variance compared to individuals, however the variance dropped significantly when they used the sommelier card. The effect of sommelier card reducing the variance was observed only in pairs, individuals did not seem to benefit from the cultural linguistic tool. Analysis of descriptions generated with the aid of sommelier cards shows that pairs were more coherent and discriminative than individuals. The findings are discussed in terms of global properties and dynamics of collective systems when constrained by different types of cultural practices. PMID:27729875

X-Eye: a novel wearable vision system

NASA Astrophysics Data System (ADS)

Wang, Yuan-Kai; Fan, Ching-Tang; Chen, Shao-Ang; Chen, Hou-Ye

2011-03-01

This paper proposes a smart portable device, named the X-Eye, which provides a gesture interface with a small size but a large display for the application of photo capture and management. The wearable vision system is implemented with embedded systems and can achieve real-time performance. The hardware of the system includes an asymmetric dualcore processer with an ARM core and a DSP core. The display device is a pico projector which has a small volume size but can project large screen size. A triple buffering mechanism is designed for efficient memory management. Software functions are partitioned and pipelined for effective execution in parallel. The gesture recognition is achieved first by a color classification which is based on the expectation-maximization algorithm and Gaussian mixture model (GMM). To improve the performance of the GMM, we devise a LUT (Look Up Table) technique. Fingertips are extracted and geometrical features of fingertip's shape are matched to recognize user's gesture commands finally. In order to verify the accuracy of the gesture recognition module, experiments are conducted in eight scenes with 400 test videos including the challenge of colorful background, low illumination, and flickering. The processing speed of the whole system including the gesture recognition is with the frame rate of 22.9FPS. Experimental results give 99% recognition rate. The experimental results demonstrate that this small-size large-screen wearable system has effective gesture interface with real-time performance.

Gaze Dynamics in the Recognition of Facial Expressions of Emotion.

PubMed

Barabanschikov, Vladimir A

2015-01-01

We studied preferably fixated parts and features of human face in the process of recognition of facial expressions of emotion. Photographs of facial expressions were used. Participants were to categorize these as basic emotions; during this process, eye movements were registered. It was found that variation in the intensity of an expression is mirrored in accuracy of emotion recognition; it was also reflected by several indices of oculomotor function: duration of inspection of certain areas of the face, its upper and bottom or right parts, right and left sides; location, number and duration of fixations, viewing trajectory. In particular, for low-intensity expressions, right side of the face was found to be attended predominantly (right-side dominance); the right-side dominance effect, was, however, absent for expressions of high intensity. For both low- and high-intensity expressions, upper face part was predominantly fixated, though with greater fixation of high-intensity expressions. The majority of trials (70%), in line with findings in previous studies, revealed a V-shaped pattern of inspection trajectory. No relationship, between accuracy of recognition of emotional expressions, was found, though, with either location and duration of fixations or pattern of gaze directedness in the face. © The Author(s) 2015.

New pattern recognition system in the e-nose for Chinese spirit identification

NASA Astrophysics Data System (ADS)

Hui, Zeng; Qiang, Li; Yu, Gu

2016-02-01

This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

Expanding the universe of cytokines and pattern recognition receptors: galectins and glycans in innate immunity.

PubMed

Cerliani, Juan P; Stowell, Sean R; Mascanfroni, Iván D; Arthur, Connie M; Cummings, Richard D; Rabinovich, Gabriel A

2011-02-01

Effective immunity relies on the recognition of pathogens and tumors by innate immune cells through diverse pattern recognition receptors (PRRs) that lead to initiation of signaling processes and secretion of pro- and anti-inflammatory cytokines. Galectins, a family of endogenous lectins widely expressed in infected and neoplastic tissues have emerged as part of the portfolio of soluble mediators and pattern recognition receptors responsible for eliciting and controlling innate immunity. These highly conserved glycan-binding proteins can control immune cell processes through binding to specific glycan structures on pathogens and tumors or by acting intracellularly via modulation of selective signaling pathways. Recent findings demonstrate that various galectin family members influence the fate and physiology of different innate immune cells including polymorphonuclear neutrophils, mast cells, macrophages, and dendritic cells. Moreover, several pathogens may actually utilize galectins as a mechanism of host invasion. In this review, we aim to highlight and integrate recent discoveries that have led to our current understanding of the role of galectins in host-pathogen interactions and innate immunity. Challenges for the future will embrace the rational manipulation of galectin-glycan interactions to instruct and shape innate immunity during microbial infections, inflammation, and cancer.

The Word Shape Hypothesis Re-Examined: Evidence for an External Feature Advantage in Visual Word Recognition

ERIC Educational Resources Information Center

Beech, John R.; Mayall, Kate A.

2005-01-01

This study investigates the relative roles of internal and external letter features in word recognition. In Experiment 1 the efficacy of outer word fragments (words with all their horizontal internal features removed) was compared with inner word fragments (words with their outer features removed) as primes in a forward masking paradigm. These…

Representations of Shape in Object Recognition and Long-Term Visual Memory

DTIC Science & Technology

1993-02-11

in anything other than linguistic terms ( Biederman , 1987 , for example). STATUS 1. Viewpoint-Dependent Features in Object Representation Tarr and...is object- based orientation-independent representations sufficient for "basic-level" categorization ( Biederman , 1987 ; Corballis, 1988). Alternatively...space. REFERENCES Biederman , I. ( 1987 ). Recognition-by-components: A theory of human image understanding. Psychological Review, 94,115-147. Cooper, L

Neural network classification technique and machine vision for bread crumb grain evaluation

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.; Chung, O. K.; Caley, M.

1995-10-01

Bread crumb grain was studied to develop a model for pattern recognition of bread baked at Hard Winter Wheat Quality Laboratory (HWWQL), Grain Marketing and Production Research Center (GMPRC). Images of bread slices were acquired with a scanner in a 512 multiplied by 512 format. Subimages in the central part of the slices were evaluated by several features such as mean, determinant, eigen values, shape of a slice and other crumb features. Derived features were used to describe slices and loaves. Neural network programs of MATLAB package were used for data analysis. Learning vector quantization method and multivariate discriminant analysis were applied to bread slices from what of different sources. A training and test sets of different bread crumb texture classes were obtained. The ranking of subimages was well correlated with visual judgement. The performance of different models on slice recognition rate was studied to choose the best model. The recognition of classes created according to human judgement with image features was low. Recognition of arbitrarily created classes, according to porosity patterns, with several feature patterns was approximately 90%. Correlation coefficient was approximately 0.7 between slice shape features and loaf volume.

Tolerance for distorted faces: challenges to a configural processing account of familiar face recognition.

PubMed

Sandford, Adam; Burton, A Mike

2014-09-01

Face recognition is widely held to rely on 'configural processing', an analysis of spatial relations between facial features. We present three experiments in which viewers were shown distorted faces, and asked to resize these to their correct shape. Based on configural theories appealing to metric distances between features, we reason that this should be an easier task for familiar than unfamiliar faces (whose subtle arrangements of features are unknown). In fact, participants were inaccurate at this task, making between 8% and 13% errors across experiments. Importantly, we observed no advantage for familiar faces: in one experiment participants were more accurate with unfamiliars, and in two experiments there was no difference. These findings were not due to general task difficulty - participants were able to resize blocks of colour to target shapes (squares) more accurately. We also found an advantage of familiarity for resizing other stimuli (brand logos). If configural processing does underlie face recognition, these results place constraints on the definition of 'configural'. Alternatively, familiar face recognition might rely on more complex criteria - based on tolerance to within-person variation rather than highly specific measurement. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic recognition of surface landmarks of anatomical structures of back and posture

NASA Astrophysics Data System (ADS)

Michoński, Jakub; Glinkowski, Wojciech; Witkowski, Marcin; Sitnik, Robert

2012-05-01

Faulty postures, scoliosis and sagittal plane deformities should be detected as early as possible to apply preventive and treatment measures against major clinical consequences. To support documentation of the severity of deformity and diminish x-ray exposures, several solutions utilizing analysis of back surface topography data were introduced. A novel approach to automatic recognition and localization of anatomical landmarks of the human back is presented that may provide more repeatable results and speed up the whole procedure. The algorithm was designed as a two-step process involving a statistical model built upon expert knowledge and analysis of three-dimensional back surface shape data. Voronoi diagram is used to connect mean geometric relations, which provide a first approximation of the positions, with surface curvature distribution, which further guides the recognition process and gives final locations of landmarks. Positions obtained using the developed algorithms are validated with respect to accuracy of manual landmark indication by experts. Preliminary validation proved that the landmarks were localized correctly, with accuracy depending mostly on the characteristics of a given structure. It was concluded that recognition should mainly take into account the shape of the back surface, putting as little emphasis on the statistical approximation as possible.

3D automatic anatomy segmentation based on iterative graph-cut-ASM.

PubMed

Chen, Xinjian; Bagci, Ulas

2011-08-01

This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al. [Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 degrees and 0.03, and over all foot bones are about 3.5709 mm, 0.35 degrees and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s. The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min.

Phase effects in masking by harmonic complexes: speech recognition.

PubMed

Deroche, Mickael L D; Culling, John F; Chatterjee, Monita

2013-12-01

Harmonic complexes that generate highly modulated temporal envelopes on the basilar membrane (BM) mask a tone less effectively than complexes that generate relatively flat temporal envelopes, because the non-linear active gain of the BM selectively amplifies a low-level tone in the dips of a modulated masker envelope. The present study examines a similar effect in speech recognition. Speech reception thresholds (SRTs) were measured for a voice masked by harmonic complexes with partials in sine phase (SP) or in random phase (RP). The masker's fundamental frequency (F0) was 50, 100 or 200 Hz. SRTs were considerably lower for SP than for RP maskers at 50-Hz F0, but the two converged at 100-Hz F0, while at 200-Hz F0, SRTs were a little higher for SP than RP maskers. The results were similar whether the target voice was male or female and whether the masker's spectral profile was flat or speech-shaped. Although listening in the masker dips has been shown to play a large role for artificial stimuli such as Schroeder-phase complexes at high levels, it contributes weakly to speech recognition in the presence of harmonic maskers with different crest factors at more moderate sound levels (65 dB SPL). Copyright © 2013 Elsevier B.V. All rights reserved.

Modeling the preferred shapes of polyamine transporter ligands and dihydromotuporamine-C mimics: shovel versus hoe.

PubMed

Breitbeil, Fred; Kaur, Navneet; Delcros, Jean-Guy; Martin, Bénédicte; Abboud, Khalil A; Phanstiel, Otto

2006-04-20

Preferred conformers generated from motuporamine and anthracene-polyamine derivatives provided insight into the shapes associated with polyamine transporter (PAT) recognition and potentially dihydromotuporamine C (4a) bioactivity. Molecular modeling revealed that N(1)-(anthracen-9-ylmethyl)-3,3-triamine (6a), N(1)-(anthracen-9-ylmethyl)-4,4-triamine (6b), N(1)-(anthracen-9-ylmethyl)-N(1)-ethyl-3,3-triamine (7a), N(1)-(anthracen-9-ylmethyl)-N(1)-ethyl-4,4-triamine (7b), and 4a all preferred a hoe motif. This hoe shape was defined by the all-anti polyamine shaft extending above the relatively flat, appended ring system. The hoe geometry was also inferred by the (1)H NMR spectrum of the free amine of 7a (CDCl(3)), which showed a strong shielding effect of the anthracene ring on the chemical shifts associated with the appended polyamine chain. This shielding effect was found to be independent over a broad concentration range of 7a, which also supported an intramolecular phenomenon. The degree of substitution at the N(1)-position seems to be an important determinant of both the molecular shape preferences and biological activity of anthracenylmethyl-polyamine conjugates.

Influence of Stimulus Symmetry and Complexity upon Haptic Scanning Strategies During Detection, Learning and Recognition Tasks.

ERIC Educational Resources Information Center

Locher, Paul J.; Simmons, Roger W.

Two experiments were conducted to investigate the perceptual processes involved in haptic exploration of randomly generated shapes. Experiment one required subjects to detect symmetrical or asymmetrical characteristics of individually presented plastic shapes, also varying in complexity. Scanning time for both symmetrical and asymmetrical shapes…

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

A New Minimum Trees-Based Approach for Shape Matching with Improved Time Computing: Application to Graphical Symbols Recognition

NASA Astrophysics Data System (ADS)

Franco, Patrick; Ogier, Jean-Marc; Loonis, Pierre; Mullot, Rémy

Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longer operates in the image space but in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discussed and justified. The experimental results led on the GREC2003 database show that the proposed method is characterized by a good discrimination power, a real robustness to noise with an acceptable time computing.

Two-dimensional shape classification using generalized Fourier representation and neural networks

NASA Astrophysics Data System (ADS)

Chodorowski, Artur; Gustavsson, Tomas; Mattsson, Ulf

2000-04-01

A shape-based classification method is developed based upon the Generalized Fourier Representation (GFR). GFR can be regarded as an extension of traditional polar Fourier descriptors, suitable for description of closed objects, both convex and concave, with or without holes. Explicit relations of GFR coefficients to regular moments, moment invariants and affine moment invariants are given in the paper. The dual linear relation between GFR coefficients and regular moments was used to compare shape features derive from GFR descriptors and Hu's moment invariants. the GFR was then applied to a clinical problem within oral medicine and used to represent the contours of the lesions in the oral cavity. The lesions studied were leukoplakia and different forms of lichenoid reactions. Shape features were extracted from GFR coefficients in order to classify potentially cancerous oral lesions. Alternative classifiers were investigated based on a multilayer perceptron with different architectures and extensions. The overall classification accuracy for recognition of potentially cancerous oral lesions when using neural network classifier was 85%, while the classification between leukoplakia and reticular lichenoid reactions gave 96% (5-fold cross-validated) recognition rate.

Classification of C2C12 cells at differentiation by convolutional neural network of deep learning using phase contrast images.

PubMed

Niioka, Hirohiko; Asatani, Satoshi; Yoshimura, Aina; Ohigashi, Hironori; Tagawa, Seiichi; Miyake, Jun

2018-01-01

In the field of regenerative medicine, tremendous numbers of cells are necessary for tissue/organ regeneration. Today automatic cell-culturing system has been developed. The next step is constructing a non-invasive method to monitor the conditions of cells automatically. As an image analysis method, convolutional neural network (CNN), one of the deep learning method, is approaching human recognition level. We constructed and applied the CNN algorithm for automatic cellular differentiation recognition of myogenic C2C12 cell line. Phase-contrast images of cultured C2C12 are prepared as input dataset. In differentiation process from myoblasts to myotubes, cellular morphology changes from round shape to elongated tubular shape due to fusion of the cells. CNN abstract the features of the shape of the cells and classify the cells depending on the culturing days from when differentiation is induced. Changes in cellular shape depending on the number of days of culture (Day 0, Day 3, Day 6) are classified with 91.3% accuracy. Image analysis with CNN has a potential to realize regenerative medicine industry.

Combining heterogenous features for 3D hand-held object recognition

NASA Astrophysics Data System (ADS)

Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

2014-10-01

Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

A split recognition mode combined with cascade signal amplification strategy for highly specific, sensitive detection of microRNA.

PubMed

Wang, Rui; Wang, Lei; Zhao, Haiyan; Jiang, Wei

2016-12-15

MicroRNAs (miRNAs) are vital for many biological processes and have been regarded as cancer biomarkers. Specific and sensitive detection of miRNAs is essential for cancer diagnosis and therapy. Herein, a split recognition mode combined with cascade signal amplification strategy is developed for highly specific and sensitive detection of miRNA. The split recognition mode possesses two specific recognition processes, which are based on toehold-mediated strand displacement reaction (TSDR) and direct hybridization reaction. Two recognition probes, hairpin probe (HP) with overhanging toehold domain and assistant probe (AP), are specially designed. Firstly, the toehold domain of HP and AP recognize part of miRNA simultaneously, accompanied with TSDR to unfold the HP and form the stable DNA Y-shaped junction structure (YJS). Then, the AP in YJS can further act as primer to initiate strand displacement amplification, releasing numerous trigger sequences. Finally, the trigger sequences hybridize with padlock DNA to initiate circular rolling circle amplification and generate enhanced fluorescence responses. In this strategy, the dual recognition effect of split recognition mode guarantees the excellent selectivity to discriminate let-7b from high-homology sequences. Furthermore, the high amplification efficiency of cascade signal amplification guarantees a high sensitivity with the detection limit of 3.2 pM and the concentration of let-7b in total RNA sample extracted from Hela cells is determined. These results indicate our strategy will be a promising miRNA detection strategy in clinical diagnosis and disease treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

Online 3D Ear Recognition by Combining Global and Local Features.

PubMed

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Online 3D Ear Recognition by Combining Global and Local Features

PubMed Central

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%. PMID:27935955

Vision-based object detection and recognition system for intelligent vehicles

NASA Astrophysics Data System (ADS)

Ran, Bin; Liu, Henry X.; Martono, Wilfung

1999-01-01

Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

Facial patterns in a tropical social wasp correlate with colony membership

NASA Astrophysics Data System (ADS)

Baracchi, David; Turillazzi, Stefano; Chittka, Lars

2016-10-01

Social insects excel in discriminating nestmates from intruders, typically relying on colony odours. Remarkably, some wasp species achieve such discrimination using visual information. However, while it is universally accepted that odours mediate a group level recognition, the ability to recognise colony members visually has been considered possible only via individual recognition by which wasps discriminate `friends' and `foes'. Using geometric morphometric analysis, which is a technique based on a rigorous statistical theory of shape allowing quantitative multivariate analyses on structure shapes, we first quantified facial marking variation of Liostenogaster flavolineata wasps. We then compared this facial variation with that of chemical profiles (generated by cuticular hydrocarbons) within and between colonies. Principal component analysis and discriminant analysis applied to sets of variables containing pure shape information showed that despite appreciable intra-colony variation, the faces of females belonging to the same colony resemble one another more than those of outsiders. This colony-specific variation in facial patterns was on a par with that observed for odours. While the occurrence of face discrimination at the colony level remains to be tested by behavioural experiments, overall our results suggest that, in this species, wasp faces display adequate information that might be potentially perceived and used by wasps for colony level recognition.

DBSCAN-based ROI extracted from SAR images and the discrimination of multi-feature ROI

NASA Astrophysics Data System (ADS)

He, Xin Yi; Zhao, Bo; Tan, Shu Run; Zhou, Xiao Yang; Jiang, Zhong Jin; Cui, Tie Jun

2009-10-01

The purpose of the paper is to extract the region of interest (ROI) from the coarse detected synthetic aperture radar (SAR) images and discriminate if the ROI contains a target or not, so as to eliminate the false alarm, and prepare for the target recognition. The automatic target clustering is one of the most difficult tasks in the SAR-image automatic target recognition system. The density-based spatial clustering of applications with noise (DBSCAN) relies on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN was first used in the SAR image processing, which has many excellent features: only two insensitivity parameters (radius of neighborhood and minimum number of points) are needed; clusters of arbitrary shapes which fit in with the coarse detected SAR images can be discovered; and the calculation time and memory can be reduced. In the multi-feature ROI discrimination scheme, we extract several target features which contain the geometry features such as the area discriminator and Radon-transform based target profile discriminator, the distribution characteristics such as the EFF discriminator, and the EM scattering property such as the PPR discriminator. The synthesized judgment effectively eliminates the false alarms.

The Precise and Efficient Identification of Medical Order Forms Using Shape Trees

NASA Astrophysics Data System (ADS)

Henker, Uwe; Petersohn, Uwe; Ultsch, Alfred

A powerful and flexible technique to identify, classify and process documents using images from a scanning process is presented. The types of documents can be described to the system as a set of differentiating features in a case base using shape trees. The features are filtered and abstracted from an extremely reduced scanner image of the document. Classification rules are stored with the cases to enable precise recognition and further mark reading and Optical Character Recognition (OCR) process. The method is implemented in a system which actually processes the majority of requests for medical lab procedures in Germany. A large practical experiment with data from practitioners was performed. An average of 97% of the forms were correctly identified; none were identified incorrectly. This meets the quality requirements for most medical applications. The modular description of the recognition process allows for a flexible adaptation of future changes to the form and content of the document’s structures.

Mechanism of Origin DNA Recognition and Assembly of an Initiator-Helicase Complex by SV40 Large Tumor Antigen

PubMed Central

Chang, Y. Paul; Xu, Meng; Machado, Ana Carolina Dantas; Yu, Xian Jessica; Rohs, Remo; Chen, Xiaojiang S.

2013-01-01

SUMMARY The DNA tumor virus Simian virus 40 (SV40) is a model system for studying eukaryotic replication. SV40 large tumor antigen (LTag) is the initiator/helicase that is essential for genome replication. LTag recognizes and assembles at the viral replication origin. We determined the structure of two multidomain LTag subunits bound to origin DNA. The structure reveals that the origin binding domains (OBDs) and Zn and AAA+ domains are involved in origin recognition and assembly. Notably, the OBDs recognize the origin in an unexpected manner. The histidine residues of the AAA+ domains insert into a narrow minor groove region with enhanced negative electrostatic potential. Computational analysis indicates that this region is intrinsically narrow, demonstrating the role of DNA shape readout in origin recognition. Our results provide important insights into the assembly of the LTag initiator/ helicase at the replication origin and suggest that histidine contacts with the minor groove serve as a mechanism of DNA shape readout. PMID:23545501

Bio-recognitive photonics of a DNA-guided organic semiconductor

PubMed Central

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA–DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an ‘inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA–DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition. PMID:26725969

Bio-recognitive photonics of a DNA-guided organic semiconductor.

PubMed

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor

NASA Astrophysics Data System (ADS)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Increased Alpha-Band Power during the Retention of Shapes and Shape-Location Associations in Visual Short-Term Memory

PubMed Central

Johnson, Jeffrey S.; Sutterer, David W.; Acheson, Daniel J.; Lewis-Peacock, Jarrod A.; Postle, Bradley R.

2011-01-01

Studies exploring the role of neural oscillations in cognition have revealed sustained increases in alpha-band (~8–14 Hz) power during the delay period of delayed-recognition short-term memory tasks. These increases have been proposed to reflect the inhibition, for example, of cortical areas representing task-irrelevant information, or of potentially interfering representations from previous trials. Another possibility, however, is that elevated delay-period alpha-band power (DPABP) reflects the selection and maintenance of information, rather than, or in addition to, the inhibition of task-irrelevant information. In the present study, we explored these possibilities using a delayed-recognition paradigm in which the presence and task relevance of shape information was systematically manipulated across trial blocks and electroencephalographic was used to measure alpha-band power. In the first trial block, participants remembered locations marked by identical black circles. The second block featured the same instructions, but locations were marked by unique shapes. The third block featured the same stimulus presentation as the second, but with pretrial instructions indicating, on a trial-by-trial basis, whether memory for shape or location was required, the other dimension being irrelevant. In the final block, participants remembered the unique pairing of shape and location for each stimulus. Results revealed minimal DPABP in each of the location-memory conditions, whether locations were marked with identical circles or with unique task-irrelevant shapes. In contrast, alpha-band power increases were observed in both the shape-memory condition, in which location was task irrelevant, and in the critical final condition, in which both shape and location were task relevant. These results provide support for the proposal that alpha-band oscillations reflect the retention of shape information and/or shape–location associations in short-term memory. PMID:21713012

Integration trumps selection in object recognition.

PubMed

Saarela, Toni P; Landy, Michael S

2015-03-30

Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integration trumps selection in object recognition

PubMed Central

Saarela, Toni P.; Landy, Michael S.

2015-01-01

Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

Pattern recognition for Space Applications Center director's discretionary fund

NASA Technical Reports Server (NTRS)

Singley, M. E.

1984-01-01

Results and conclusions are presented on the application of recent developments in pattern recognition to spacecraft star mapping systems. Sensor data for two representative starfields are processed by an adaptive shape-seeking version of the Fc-V algorithm with good results. Cluster validity measures are evaluated, but not found especially useful to this application. Recommendations are given two system configurations worthy of additional study,

[The effects of normal aging on face naming and recognition of famous people: battery 75].

PubMed

Pluchon, C; Simonnet, E; Toullat, G; Gil, R

2002-07-01

The difficulty to recall proper nouns is often something elderly people complain about. Thus, we tried to build and standardize a tool that could allow a quantified estimation of the naming and recognition abilities about famous people faces, specifying the part of gender, age and cultural level for each kind of test. The performances of 542 subjects divided in 3 age brackets and 3 academic knowledge levels were analysed. To carry out the test material, the artistic team of the Grevin Museum (Paris) was called upon. Their work offers a homogeneous way to shape famous people faces. One same person thus photographed 75 characters from different social categories with the same conditions of light, during only one day. The results of the study show that men perform better than women as concerns naming task, but that there's no difference between genders as concerns recognition task. Recognition performances are significantly better whatever the age, the gender and the cultural level may be. Generally, performances are all the more better since subjects are younger and have a higher cultural level. Our study then confirms the fact that normal aging goes hand in hand with rising difficulties to name faces. Moreover, results tend to show that recognition of faces remains better preserved and that the greater disability to recall a name is linked to difficulties in lexical accessing.

Permutation coding technique for image recognition systems.

PubMed

Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

2006-11-01

A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.

StreetScenes: Towards Scene Understanding in Still Images

DTIC Science & Technology

2006-05-01

Riesenhuber and Poggio’s C1 features from their Standard Model [91], Berg and Malik’s geometric blur [7], Belongie et al.’s shape context [5], and Dalal and...images was performed by payed employees of the Center for Biological and Computational Learning (CBCL) during the period between January 2003 and July...single example by feature replacement. In CVPR, 2005. [5] S. Belongie , J. Malik, and J. Puzicha. Shape matching and object recognition using shape

Application of 3D Zernike descriptors to shape-based ligand similarity searching.

PubMed

Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

2009-12-17

The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

Application of 3D Zernike descriptors to shape-based ligand similarity searching

PubMed Central

2009-01-01

Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD. PMID:20150998

Use of pattern recognition and neural networks for non-metric sex diagnosis from lateral shape of calvarium: an innovative model for computer-aided diagnosis in forensic and physical anthropology.

PubMed

Cavalli, Fabio; Lusnig, Luca; Trentin, Edmondo

2017-05-01

Sex determination on skeletal remains is one of the most important diagnosis in forensic cases and in demographic studies on ancient populations. Our purpose is to realize an automatic operator-independent method to determine the sex from the bone shape and to test an intelligent, automatic pattern recognition system in an anthropological domain. Our multiple-classifier system is based exclusively on the morphological variants of a curve that represents the sagittal profile of the calvarium, modeled via artificial neural networks, and yields an accuracy higher than 80 %. The application of this system to other bone profiles is expected to further improve the sensibility of the methodology.

Ensemble training to improve recognition using 2D ear

NASA Astrophysics Data System (ADS)

Middendorff, Christopher; Bowyer, Kevin W.

2009-05-01

The ear has gained popularity as a biometric feature due to the robustness of the shape over time and across emotional expression. Popular methods of ear biometrics analyze the ear as a whole, leaving these methods vulnerable to error due to occlusion. Many researchers explore ear recognition using an ensemble, but none present a method for designing the individual parts that comprise the ensemble. In this work, we introduce a method of modifying the ensemble shapes to improve performance. We determine how different properties of an ensemble training system can affect overall performance. We show that ensembles built from small parts will outperform ensembles built with larger parts, and that incorporating a large number of parts improves the performance of the ensemble.

L-split marker for augmented reality in aircraft assembly

NASA Astrophysics Data System (ADS)

Han, Pengfei; Zhao, Gang

2016-04-01

In order to improve the performance of conventional square markers widely used by marker-based augmented reality systems in aircraft assembly environments, an L-split marker is proposed. Every marker consists of four separate L-shaped parts and each of them contains partial information about the marker. Geometric features of the L-shape, which are more discriminate than the symmetrical square shape adopted by conventional markers, are used to detect proposed markers from the camera images effectively. The marker is split into four separate parts in order to improve the robustness to occlusion and curvature to some extent. The registration process can be successfully completed as long as three parts are detected (up to about 80% of the area could be occluded). Moreover, when we attach the marker on nonplanar surfaces, the curvature status of the marker can be roughly analyzed with every part's normal direction, which can be obtained since their six corners have been explicitly determined in the previous detection process. And based on the marker design, new detection and recognition algorithms are proposed and detailed. The experimental results show that the marker and the algorithms are effective.

Document image retrieval through word shape coding.

PubMed

Lu, Shijian; Li, Linlin; Tan, Chew Lim

2008-11-01

This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.

Memory color of natural familiar objects: effects of surface texture and 3-D shape.

PubMed

Vurro, Milena; Ling, Yazhu; Hurlbert, Anya C

2013-06-28

Natural objects typically possess characteristic contours, chromatic surface textures, and three-dimensional shapes. These diagnostic features aid object recognition, as does memory color, the color most associated in memory with a particular object. Here we aim to determine whether polychromatic surface texture, 3-D shape, and contour diagnosticity improve memory color for familiar objects, separately and in combination. We use solid three-dimensional familiar objects rendered with their natural texture, which participants adjust in real time to match their memory color for the object. We analyze mean, accuracy, and precision of the memory color settings relative to the natural color of the objects under the same conditions. We find that in all conditions, memory colors deviate slightly but significantly in the same direction from the natural color. Surface polychromaticity, shape diagnosticity, and three dimensionality each improve memory color accuracy, relative to uniformly colored, generic, or two-dimensional shapes, respectively. Shape diagnosticity improves the precision of memory color also, and there is a trend for polychromaticity to do so as well. Differently from other studies, we find that the object contour alone also improves memory color. Thus, enhancing the naturalness of the stimulus, in terms of either surface or shape properties, enhances the accuracy and precision of memory color. The results support the hypothesis that memory color representations are polychromatic and are synergistically linked with diagnostic shape representations.

A new look at emotion perception: Concepts speed and shape facial emotion recognition.

PubMed

Nook, Erik C; Lindquist, Kristen A; Zaki, Jamil

2015-10-01

Decades ago, the "New Look" movement challenged how scientists thought about vision by suggesting that conceptual processes shape visual perceptions. Currently, affective scientists are likewise debating the role of concepts in emotion perception. Here, we utilized a repetition-priming paradigm in conjunction with signal detection and individual difference analyses to examine how providing emotion labels-which correspond to discrete emotion concepts-affects emotion recognition. In Study 1, pairing emotional faces with emotion labels (e.g., "sad") increased individuals' speed and sensitivity in recognizing emotions. Additionally, individuals with alexithymia-who have difficulty labeling their own emotions-struggled to recognize emotions based on visual cues alone, but not when emotion labels were provided. Study 2 replicated these findings and further demonstrated that emotion concepts can shape perceptions of facial expressions. Together, these results suggest that emotion perception involves conceptual processing. We discuss the implications of these findings for affective, social, and clinical psychology. (c) 2015 APA, all rights reserved).

Bypassing adverse injection reactions to nanoparticles through shape modification and attachment to erythrocytes

NASA Astrophysics Data System (ADS)

Wibroe, Peter Popp; Anselmo, Aaron C.; Nilsson, Per H.; Sarode, Apoorva; Gupta, Vivek; Urbanics, Rudolf; Szebeni, Janos; Hunter, Alan Christy; Mitragotri, Samir; Mollnes, Tom Eirik; Moghimi, Seyed Moein

2017-07-01

Intravenously injected nanopharmaceuticals, including PEGylated nanoparticles, induce adverse cardiopulmonary reactions in sensitive human subjects, and these reactions are highly reproducible in pigs. Although the underlying mechanisms are poorly understood, roles for both the complement system and reactive macrophages have been implicated. Here, we show the dominance and importance of robust pulmonary intravascular macrophage clearance of nanoparticles in mediating adverse cardiopulmonary distress in pigs irrespective of complement activation. Specifically, we show that delaying particle recognition by macrophages within the first few minutes of injection overcomes adverse reactions in pigs using two independent approaches. First, we changed the particle geometry from a spherical shape (which triggers cardiopulmonary distress) to either rod- or disk-shape morphology. Second, we physically adhered spheres to the surface of erythrocytes. These strategies, which are distinct from commonly leveraged stealth engineering approaches such as nanoparticle surface functionalization with poly(ethylene glycol) and/or immunological modulators, prevent robust macrophage recognition, resulting in the reduction or mitigation of adverse cardiopulmonary distress associated with nanopharmaceutical administration.

[Visual Texture Agnosia in Humans].

PubMed

Suzuki, Kyoko

2015-06-01

Visual object recognition requires the processing of both geometric and surface properties. Patients with occipital lesions may have visual agnosia, which is impairment in the recognition and identification of visually presented objects primarily through their geometric features. An analogous condition involving the failure to recognize an object by its texture may exist, which can be called visual texture agnosia. Here we present two cases with visual texture agnosia. Case 1 had left homonymous hemianopia and right upper quadrantanopia, along with achromatopsia, prosopagnosia, and texture agnosia, because of damage to his left ventromedial occipitotemporal cortex and right lateral occipito-temporo-parietal cortex due to multiple cerebral embolisms. Although he showed difficulty matching and naming textures of real materials, he could readily name visually presented objects by their contours. Case 2 had right lower quadrantanopia, along with impairment in stereopsis and recognition of texture in 2D images, because of subcortical hemorrhage in the left occipitotemporal region. He failed to recognize shapes based on texture information, whereas shape recognition based on contours was well preserved. Our findings, along with those of three reported cases with texture agnosia, indicate that there are separate channels for processing texture, color, and geometric features, and that the regions around the left collateral sulcus are crucial for texture processing.

Real-time color/shape-based traffic signs acquisition and recognition system

NASA Astrophysics Data System (ADS)

Saponara, Sergio

2013-02-01

A real-time system is proposed to acquire from an automotive fish-eye CMOS camera the traffic signs, and provide their automatic recognition on the vehicle network. Differently from the state-of-the-art, in this work color-detection is addressed exploiting the HSI color space which is robust to lighting changes. Hence the first stage of the processing system implements fish-eye correction and RGB to HSI transformation. After color-based detection a noise deletion step is implemented and then, for the classification, a template-based correlation method is adopted to identify potential traffic signs, of different shapes, from acquired images. Starting from a segmented-image a matching with templates of the searched signs is carried out using a distance transform. These templates are organized hierarchically to reduce the number of operations and hence easing real-time processing for several types of traffic signs. Finally, for the recognition of the specific traffic sign, a technique based on extraction of signs characteristics and thresholding is adopted. Implemented on DSP platform the system recognizes traffic signs in less than 150 ms at a distance of about 15 meters from 640x480-pixel acquired images. Tests carried out with hundreds of images show a detection and recognition rate of about 93%.

Body-Earth Mover's Distance: A Matching-Based Approach for Sleep Posture Recognition.

PubMed

Xu, Xiaowei; Lin, Feng; Wang, Aosen; Hu, Yu; Huang, Ming-Chun; Xu, Wenyao

2016-10-01

Sleep posture is a key component in sleep quality assessment and pressure ulcer prevention. Currently, body pressure analysis has been a popular method for sleep posture recognition. In this paper, a matching-based approach, Body-Earth Mover's Distance (BEMD), for sleep posture recognition is proposed. BEMD treats pressure images as weighted 2D shapes, and combines EMD and Euclidean distance for similarity measure. Compared with existing work, sleep posture recognition is achieved with posture similarity rather than multiple features for specific postures. A pilot study is performed with 14 persons for six different postures. The experimental results show that the proposed BEMD can achieve 91.21% accuracy, which outperforms the previous method with an improvement of 8.01%.

Character context: a shape descriptor for Arabic handwriting recognition

NASA Astrophysics Data System (ADS)

Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu

2017-11-01

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

F-16 Low Altitude Navigation and Targeting Infrared System for Night (LANTIRN) and the Night Close Air Support (CAS) Mission

DTIC Science & Technology

1989-06-02

physical reference can be a natural feature, river bend, distinctly shaped wooded area, or lake. Artificial references such as colored smoke or...fluorescent ground panels can also be placed instead of, or as an aid to recognition of the natural feature.ដ> But, artificial references that are effective...Government Printin-gOffice, 1959. Central Intelligence Agenc7. National Intellignece Survey, East Germany, Section 23, Weather and Climate. Washington

Understanding the molecular differential recognition of muramyl peptide ligands by LRR domains of human NOD receptors.

PubMed

Vijayrajratnam, Sukhithasri; Pushkaran, Anju Choorakottayil; Balakrishnan, Aathira; Vasudevan, Anil Kumar; Biswas, Raja; Mohan, Chethampadi Gopi

2017-07-27

Human nucleotide-binding oligomerization domain proteins, hNOD1 and hNOD2, are host intracellular receptors with C-terminal leucine-rich repeat (LRR) domains, which recognize specific bacterial peptidoglycan (PG) fragments as their ligands. The specificity of this recognition is dependent on the third amino acid of the stem peptide of the PG ligand, which is usually meso -diaminopimelic acid ( meso DAP) or l-lysine (l-Lys). Since the LRR domains of hNOD receptors had been experimentally shown to confer the PG ligand-sensing specificity, we developed three-dimensional structures of hNOD1-LRR and the hNOD2-LRR to understand the mechanism of differential recognition of muramyl peptide ligands by hNOD receptors. The hNOD1-LRR and hNOD2-LRR receptor models exhibited right-handed curved solenoid shape. The hot-spot residues experimentally proved to be critical for ligand recognition were located in the concavity of the NOD-LRR and formed the recognition site. Our molecular docking analyses and molecular electrostatic potential mapping studies explain the activation of hNOD-LRRs, in response to effective molecular interactions of PG ligands at the recognition site; and conversely, the inability of certain PG ligands to activate hNOD-LRRs, by deviations from the recognition site. Based on molecular docking studies using PG ligands, we propose few residues - G825, D826 and N850 in hNOD1-LRR and L904, G905, W931, L932 and S933 in hNOD2-LRR, evolutionarily conserved across different host species, which may play a major role in ligand recognition. Thus, our integrated experimental and computational approach elucidates the molecular basis underlying the differential recognition of PG ligands by hNOD receptors. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Pattern recognition applied to infrared images for early alerts in fog

NASA Astrophysics Data System (ADS)

Boucher, Vincent; Marchetti, Mario; Dumoulin, Jean; Cord, Aurélien

2014-09-01

Fog conditions are the cause of severe car accidents in western countries because of the poor induced visibility. Its forecast and intensity are still very difficult to predict by weather services. Infrared cameras allow to detect and to identify objects in fog while visibility is too low for eye detection. Over the past years, the implementation of cost effective infrared cameras on some vehicles has enabled such detection. On the other hand pattern recognition algorithms based on Canny filters and Hough transformation are a common tool applied to images. Based on these facts, a joint research program between IFSTTAR and Cerema has been developed to study the benefit of infrared images obtained in a fog tunnel during its natural dissipation. Pattern recognition algorithms have been applied, specifically on road signs which shape is usually associated to a specific meaning (circular for a speed limit, triangle for an alert, …). It has been shown that road signs were detected early enough in images, with respect to images in the visible spectrum, to trigger useful alerts for Advanced Driver Assistance Systems.

Aging and the Haptic Perception of Material Properties.

PubMed

Norman, J Farley; Adkins, Olivia C; Hoyng, Stevie C; Dowell, Catherine J; Pedersen, Lauren E; Gilliam, Ashley N

2016-12-01

The ability of 26 younger (mean age was 22.5 years) and older adults (mean age was 72.6 years) to haptically perceive material properties was evaluated. The participants manually explored (for 5 seconds) 42 surfaces twice and placed each of these 84 experimental stimuli into one of seven categories: paper, plastic, metal, wood, stone, fabric, and fur/leather. In general, the participants were best able to identify fur/leather and wood materials; in contrast, recognition performance was worst for stone and paper. Despite similar overall patterns of performance for younger and older participants, the younger adults' recognition accuracies were 26.5% higher. The participants' tactile acuities (assessed by tactile grating orientation discrimination) affected their ability to identify surface material. In particular, the Pearson r correlation coefficient relating the participants' grating orientation thresholds and their material identification performance was -0.8: The higher the participants' thresholds, the lower the material recognition ability. While older adults are able to effectively perceive the solid shape of environmental objects using the sense of touch, their ability to perceive surface materials is significantly compromised.

Small-Molecule-Based Self-Assembled Ligands for G-Quadruplex DNA Surface Recognition.

PubMed

Rivera-Sánchez, María Del C; García-Arriaga, Marilyn; Hobley, Gerard; Morales-de-Echegaray, Ana V; Rivera, José M

2017-10-31

Most drugs are small molecules because of their attractive pharmacokinetics, manageable development and manufacturing, and effective binding into the concave crevices of bio-macromolecules. Despite these features, they often fall short when it comes to effectively recognizing the surfaces of bio-macromolecules. One way to overcome the challenge of biomolecular surface recognition is to develop small molecules that become self-assembled ligands (SALs) prior to binding. Herein, we report SALs made from 8-aryl-2'-deoxyguanosine derivatives forming precise hydrophilic supramolecular G-quadruplexes (SGQs) with excellent size, shape, and charge complementarity to G-quadruplex DNA (QDNA). We show that only those compounds forming SGQs act as SALs, which in turn differentially stabilize QDNAs from selected oncogene promoters and the human telomeric regions. Fluorescence resonance energy-transfer melting assays are consistent with spectroscopic, calorimetric, and light scattering studies, showing the formation of a "sandwichlike" complex QDNA·SGQ·QDNA. These results open the door for the advent of SALs that recognize QDNAs and potentially the surfaces of other bio-macromolecules such as proteins.

Is Word Shape Still in Poor Shape for the Race to the Lexicon?

ERIC Educational Resources Information Center

Hill, Jessica C.

2010-01-01

Current models of normal reading behavior emphasize not only the recognition and processing of the word being fixated (n) but also processing of the upcoming parafoveal word (n + 1). Gaze contingent displays employing the boundary paradigm often mask words in order to understand how much and what type of processing is completed on the parafoveal…

3D-shape recognition and size measurement of irregular rough particles using multi-views interferometric out-of-focus imaging.

PubMed

Ouldarbi, L; Talbi, M; Coëtmellec, S; Lebrun, D; Gréhan, G; Perret, G; Brunel, M

2016-11-10

We realize simplified-tomography experiments on irregular rough particles using interferometric out-of-focus imaging. Using two angles of view, we determine the global 3D-shape, the dimensions, and the 3D-orientation of irregular rough particles whose morphologies belong to families such as sticks, plates, and crosses.

High-fidelity in vivo replication of DNA base shape mimics without Watson–Crick hydrogen bonds

PubMed Central

Delaney, James C.; Henderson, Paul T.; Helquist, Sandra A.; Morales, Juan C.; Essigmann, John M.; Kool, Eric T.

2003-01-01

We report studies testing the importance of Watson–Crick hydrogen bonding, base-pair geometry, and steric effects during DNA replication in living bacterial cells. Nonpolar DNA base shape mimics of thymine and adenine (abbreviated F and Q, respectively) were introduced into Escherichia coli by insertion into a phage genome followed by transfection of the vector into bacteria. Genetic assays showed that these two base mimics were bypassed with moderate to high efficiency in the cells and with very high efficiency under damage-response (SOS induction) conditions. Under both sets of conditions, the T-shape mimic (F) encoded genetic information in the bacteria as if it were thymine, directing incorporation of adenine opposite it with high fidelity. Similarly, the A mimic (Q) directed incorporation of thymine opposite itself with high fidelity. The data establish that Watson–Crick hydrogen bonding is not necessary for high-fidelity replication of a base pair in vivo. The results suggest that recognition of DNA base shape alone serves as the most powerful determinant of fidelity during transfer of genetic information in a living organism. PMID:12676985

Identification and detection of simple 3D objects with severely blurred vision.

PubMed

Kallie, Christopher S; Legge, Gordon E; Yu, Deyue

2012-12-05

Detecting and recognizing three-dimensional (3D) objects is an important component of the visual accessibility of public spaces for people with impaired vision. The present study investigated the impact of environmental factors and object properties on the recognition of objects by subjects who viewed physical objects with severely reduced acuity. The experiment was conducted in an indoor testing space. We examined detection and identification of simple convex objects by normally sighted subjects wearing diffusing goggles that reduced effective acuity to 20/900. We used psychophysical methods to examine the effect on performance of important environmental variables: viewing distance (from 10-24 feet, or 3.05-7.32 m) and illumination (overhead fluorescent and artificial window), and object variables: shape (boxes and cylinders), size (heights from 2-6 feet, or 0.61-1.83 m), and color (gray and white). Object identification was significantly affected by distance, color, height, and shape, as well as interactions between illumination, color, and shape. A stepwise regression analysis showed that 64% of the variability in identification could be explained by object contrast values (58%) and object visual angle (6%). When acuity is severely limited, illumination, distance, color, height, and shape influence the identification and detection of simple 3D objects. These effects can be explained in large part by the impact of these variables on object contrast and visual angle. Basic design principles for improving object visibility are discussed.

Adaptive optics to enhance target recognition

NASA Astrophysics Data System (ADS)

McAulay, Alastair D.

2012-06-01

Target recognition can be enhanced by reducing image degradation due to atmospheric turbulence. This is accomplished by an adaptive optic system. We discuss the forms of degradation when a target is viewed through the atmosphere1: scintillation from ground targets on a hot day in visible or infrared light; beam spreading and wavering around in time; atmospheric turbulence caused by motion of the target or by weather. In the case of targets we can use a beacon laser that reflects back from the target into a wavefront detector to measure the effects of turbulence on propagation to and from the target before imaging.1 A deformable mirror then corrects the wavefront shape of the transmitted, reflected or scattered data for enhanced imaging. Further, recognition of targets is enhanced by performing accurate distance measurements to localized parts of the target using lidar. Distance is obtained by sending a short pulse to the target and measuring the time for the pulse to return. There is inadequate time to scan the complete field of view so that the beam must be steered to regions of interest such as extremities of the image during image recognition. Distance is particularly valuable to recognize fine features in range along the target or when segmentation is required to separate a target from background or from other targets. We discuss the issues involved.

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

PubMed

Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

2018-02-26

The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

3D automatic anatomy segmentation based on iterative graph-cut-ASM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xinjian; Bagci, Ulas; Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10 Room 1C515, Bethesda, Maryland 20892-1182

2011-08-15

Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability ofmore » the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s. Conclusions: The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min.« less

3D automatic anatomy segmentation based on iterative graph-cut-ASM

PubMed Central

Chen, Xinjian; Bagci, Ulas

2011-01-01

Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images.Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al. [Proc. SPIE, 7259, 72590C1–72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine.Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10° and 0.03, and over all foot bones are about 3.5709 mm, 0.35° and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s.Conclusions: The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min. PMID:21928634

Faces forming traces: neurophysiological correlates of learning naturally distinctive and caricatured faces.

PubMed

Schulz, Claudia; Kaufmann, Jürgen M; Kurt, Alexander; Schweinberger, Stefan R

2012-10-15

Distinctive faces are easier to learn and recognise than typical faces. We investigated effects of natural vs. artificial distinctiveness on performance and neural correlates of face learning. Spatial caricatures of initially non-distinctive faces were created such that their rated distinctiveness matched a set of naturally distinctive faces. During learning, we presented naturally distinctive, caricatured, and non-distinctive faces for later recognition among novel faces, using different images of the same identities at learning and test. For learned faces, an advantage in performance was observed for naturally distinctive and caricatured over non-distinctive faces, with larger benefits for naturally distinctive faces. Distinctive and caricatured faces elicited more negative occipitotemporal ERPs (P200, N250) and larger centroparietal positivity (LPC) during learning. At test, earliest distinctiveness effects were again seen in the P200. In line with recent research, N250 and LPC were larger for learned than for novel faces overall. Importantly, whereas left hemispheric N250 was increased for learned naturally distinctive faces, right hemispheric N250 responded particularly to caricatured novel faces. We conclude that natural distinctiveness induces benefits to face recognition beyond those induced by exaggeration of a face's idiosyncratic shape, and that the left hemisphere in particular may mediate recognition across different images. Copyright © 2012 Elsevier Inc. All rights reserved.

Study on road sign recognition in LabVIEW

NASA Astrophysics Data System (ADS)

Panoiu, M.; Rat, C. L.; Panoiu, C.

2016-02-01

Road and traffic sign identification is a field of study that can be used to aid the development of in-car advisory systems. It uses computer vision and artificial intelligence to extract the road signs from outdoor images acquired by a camera in uncontrolled lighting conditions where they may be occluded by other objects, or may suffer from problems such as color fading, disorientation, variations in shape and size, etc. An automatic means of identifying traffic signs, in these conditions, can make a significant contribution to develop an Intelligent Transport Systems (ITS) that continuously monitors the driver, the vehicle, and the road. Road and traffic signs are characterized by a number of features which make them recognizable from the environment. Road signs are located in standard positions and have standard shapes, standard colors, and known pictograms. These characteristics make them suitable for image identification. Traffic sign identification covers two problems: traffic sign detection and traffic sign recognition. Traffic sign detection is meant for the accurate localization of traffic signs in the image space, while traffic sign recognition handles the labeling of such detections into specific traffic sign types or subcategories [1].

Automatic recognition of ship types from infrared images using superstructure moment invariants

NASA Astrophysics Data System (ADS)

Li, Heng; Wang, Xinyu

2007-11-01

Automatic object recognition is an active area of interest for military and commercial applications. In this paper, a system addressing autonomous recognition of ship types in infrared images is proposed. Firstly, an approach of segmentation based on detection of salient features of the target with subsequent shadow removing is proposed, as is the base of the subsequent object recognition. Considering the differences between the shapes of various ships mainly lie in their superstructures, we then use superstructure moment functions invariant to translation, rotation and scale differences in input patterns and develop a robust algorithm of obtaining ship superstructure. Subsequently a back-propagation neural network is used as a classifier in the recognition stage and projection images of simulated three-dimensional ship models are used as the training sets. Our recognition model was implemented and experimentally validated using both simulated three-dimensional ship model images and real images derived from video of an AN/AAS-44V Forward Looking Infrared(FLIR) sensor.

The role of lines and corners of geometric figures in recognition performance.

PubMed

Shevelev, Igor A; Kamenkovich, Viktorina M; Sharaev, George A

2003-01-01

A relative role of lines and corners of images of outline geometric figures in recognition performance was studied psychophysically. Probability of correct response to the shape of the whole figure (control) and figures with lines or corners masked to a different extent was compared. Increase in the extent of masking resulted in a drop of recognition performance that was significantly lower for figures without corners, than for figures without part of their lines. The whole 3D figures were recognized better than 2D ones, whereas the opposite relations were observed under conditions of masking. Significant gender difference in a recognition performance was found: men recognize entire and partly masked figures better than women. Possible mechanisms of relatively better recognition of figures with corners than with lines are discussed in connection with finding of high sensitivity of many neurons in the primary visual cortex to line crossing and branching.

Handwritten recognition of Tamil vowels using deep learning

NASA Astrophysics Data System (ADS)

Ram Prashanth, N.; Siddarth, B.; Ganesh, Anirudh; Naveen Kumar, Vaegae

2017-11-01

We come across a large volume of handwritten texts in our daily lives and handwritten character recognition has long been an important area of research in pattern recognition. The complexity of the task varies among different languages and it so happens largely due to the similarity between characters, distinct shapes and number of characters which are all language-specific properties. There have been numerous works on character recognition of English alphabets and with laudable success, but regional languages have not been dealt with very frequently and with similar accuracies. In this paper, we explored the performance of Deep Belief Networks in the classification of Handwritten Tamil vowels, and conclusively compared the results obtained. The proposed method has shown satisfactory recognition accuracy in light of difficulties faced with regional languages such as similarity between characters and minute nuances that differentiate them. We can further extend this to all the Tamil characters.

A depictive neural model for the representation of motion verbs.

PubMed

Rao, Sunil; Aleksander, Igor

2011-11-01

In this paper, we present a depictive neural model for the representation of motion verb semantics in neural models of visual awareness. The problem of modelling motion verb representation is shown to be one of function application, mapping a set of given input variables defining the moving object and the path of motion to a defined output outcome in the motion recognition context. The particular function-applicative implementation and consequent recognition model design presented are seen as arising from a noun-adjective recognition model enabling the recognition of colour adjectives as applied to a set of shapes representing objects to be recognised. The presence of such a function application scheme and a separately implemented position identification and path labelling scheme are accordingly shown to be the primitives required to enable the design and construction of a composite depictive motion verb recognition scheme. Extensions to the presented design to enable the representation of transitive verbs are also discussed.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Losing face: impaired discrimination of featural and configural information in the mouth region of an inverted face.

PubMed

Tanaka, James W; Kaiser, Martha D; Hagen, Simen; Pierce, Lara J

2014-05-01

Given that all faces share the same set of features-two eyes, a nose, and a mouth-that are arranged in similar configuration, recognition of a specific face must depend on our ability to discern subtle differences in its featural and configural properties. An enduring question in the face-processing literature is whether featural or configural information plays a larger role in the recognition process. To address this question, the face dimensions task was designed, in which the featural and configural properties in the upper (eye) and lower (mouth) regions of a face were parametrically and independently manipulated. In a same-different task, two faces were sequentially presented and tested in their upright or in their inverted orientation. Inversion disrupted the perception of featural size (Exp. 1), featural shape (Exp. 2), and configural changes in the mouth region, but it had relatively little effect on the discrimination of featural size and shape and configural differences in the eye region. Inversion had little effect on the perception of information in the top and bottom halves of houses (Exp. 3), suggesting that the lower-half impairment was specific to faces. Spatial cueing to the mouth region eliminated the inversion effect (Exp. 4), suggesting that participants have a bias to attend to the eye region of an inverted face. The collective findings from these experiments suggest that inversion does not differentially impair featural or configural face perceptions, but rather impairs the perception of information in the mouth region of the face.

Recognizing simple polyhedron from a perspective drawing

NASA Astrophysics Data System (ADS)

Zhang, Guimei; Chu, Jun; Miao, Jun

2009-10-01

Existed methods can't be used for recognizing simple polyhedron. In this paper, three problems are researched. First, a method for recognizing triangle and quadrilateral is introduced based on geometry and angle constraint. Then Attribute Relation Graph (ARG) is employed to describe simple polyhedron and line drawing. Last, a new method is presented to recognize simple polyhedron from a line drawing. The method filters the candidate database before matching line drawing and model, thus the recognition efficiency is improved greatly. We introduced the geometrical characteristics and topological characteristics to describe each node of ARG, so the algorithm can not only recognize polyhedrons with different shape but also distinguish between polyhedrons with the same shape but with different sizes and proportions. Computer simulations demonstrate the effectiveness of the method preliminarily.

Detecting objects in radiographs for homeland security

NASA Astrophysics Data System (ADS)

Prasad, Lakshman; Snyder, Hans

2005-05-01

We present a general scheme for segmenting a radiographic image into polygons that correspond to visual features. This decomposition provides a vectorized representation that is a high-level description of the image. The polygons correspond to objects or object parts present in the image. This characterization of radiographs allows the direct application of several shape recognition algorithms to identify objects. In this paper we describe the use of constrained Delaunay triangulations as a uniform foundational tool to achieve multiple visual tasks, namely image segmentation, shape decomposition, and parts-based shape matching. Shape decomposition yields parts that serve as tokens representing local shape characteristics. Parts-based shape matching enables the recognition of objects in the presence of occlusions, which commonly occur in radiographs. The polygonal representation of image features affords the efficient design and application of sophisticated geometric filtering methods to detect large-scale structural properties of objects in images. Finally, the representation of radiographs via polygons results in significant reduction of image file sizes and permits the scalable graphical representation of images, along with annotations of detected objects, in the SVG (scalable vector graphics) format that is proposed by the world wide web consortium (W3C). This is a textual representation that can be compressed and encrypted for efficient and secure transmission of information over wireless channels and on the Internet. In particular, our methods described here provide an algorithmic framework for developing image analysis tools for screening cargo at ports of entry for homeland security.

Distinct domains of the AVRPM3A2/F2 avirulence protein from wheat powdery mildew are involved in immune receptor recognition and putative effector function

USDA-ARS?s Scientific Manuscript database

Recognition of the AVRPM3A2/F2 avirulence protein from powdery mildew by the wheat PM3A/F immune receptor induces a hypersensitive response after coexpression in Nicotiana benthamiana. The molecular determinants of this interaction and how they shape natural AvrPm3a2/f2 allelic diversity is unknown....

System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database

NASA Astrophysics Data System (ADS)

Petpairote, Chayanut; Madarasmi, Suthep; Chamnongthai, Kosin

2018-01-01

The practical identification of individuals using facial recognition techniques requires the matching of faces with specific expressions to faces from a neutral face database. A method for facial recognition under varied expressions against neutral face samples of individuals via recognition of expression warping and the use of a virtual expression-face database is proposed. In this method, facial expressions are recognized and the input expression faces are classified into facial expression groups. To aid facial recognition, the virtual expression-face database is sorted into average facial-expression shapes and by coarse- and fine-featured facial textures. Wrinkle information is also employed in classification by using a process of masking to adjust input faces to match the expression-face database. We evaluate the performance of the proposed method using the CMU multi-PIE, Cohn-Kanade, and AR expression-face databases, and we find that it provides significantly improved results in terms of face recognition accuracy compared to conventional methods and is acceptable for facial recognition under expression variation.

Recognition of extremophilic archaeal viruses by eukaryotic cells: a promising nanoplatform from the third domain of life

PubMed Central

Uldahl, Kristine Buch; Wu, Linping; Hall, Arnaldur; Papathanasiou, Pavlos; Peng, Xu; Moghimi, Seyed Moein

2016-01-01

Viruses from the third domain of life, Archaea, exhibit unusual features including extreme stability that allow their survival in harsh environments. In addition, these species have never been reported to integrate into human or any other eukaryotic genomes, and could thus serve for exploration of novel medical nanoplatforms. Here, we selected two archaeal viruses Sulfolobus monocaudavirus 1 (SMV1) and Sulfolobus spindle shaped virus 2 (SSV2) owing to their unique spindle shape, hyperthermostable and acid-resistant nature and studied their interaction with mammalian cells. Accordingly, we followed viral uptake, intracellular trafficking and cell viability in human endothelial cells of brain (hCMEC/D3 cells) and umbilical vein (HUVEC) origin. Whereas SMV1 is efficiently internalized into both types of human cells, SSV2 differentiates between HUVECs and hCMEC/D3 cells, thus opening a path for selective cell targeting. On internalization, both viruses localize to the lysosomal compartments. Neither SMV1, nor SSV2 induced any detrimental effect on cell morphology, plasma membrane and mitochondrial functionality. This is the first study demonstrating recognition of archaeal viruses by eukaryotic cells which provides good basis for future exploration of archaeal viruses in bioengineering and development of multifunctional vectors. PMID:27892499

Application of morphological associative memories and Fourier descriptors for classification of noisy subsurface signatures

NASA Astrophysics Data System (ADS)

Ortiz, Jorge L.; Parsiani, Hamed; Tolstoy, Leonid

2004-02-01

This paper presents a method for recognition of Noisy Subsurface Images using Morphological Associative Memories (MAM). MAM are type of associative memories that use a new kind of neural networks based in the algebra system known as semi-ring. The operations performed in this algebraic system are highly nonlinear providing additional strength when compared to other transformations. Morphological associative memories are a new kind of neural networks that provide a robust performance with noisy inputs. Two representations of morphological associative memories are used called M and W matrices. M associative memory provides a robust association with input patterns corrupted by dilative random noise, while the W associative matrix performs a robust recognition in patterns corrupted with erosive random noise. The robust performance of MAM is used in combination of the Fourier descriptors for the recognition of underground objects in Ground Penetrating Radar (GPR) images. Multiple 2-D GPR images of a site are made available by NASA-SSC center. The buried objects in these images appear in the form of hyperbolas which are the results of radar backscatter from the artifacts or objects. The Fourier descriptors of the prototype hyperbola-like and shapes from non-hyperbola shapes in the sub-surface images are used to make these shapes scale-, shift-, and rotation-invariant. Typical hyperbola-like and non-hyperbola shapes are used to calculate the morphological associative memories. The trained MAMs are used to process other noisy images to detect the presence of these underground objects. The outputs from the MAM using the noisy patterns may be equal to the training prototypes, providing a positive identification of the artifacts. The results are images with recognized hyperbolas which indicate the presence of buried artifacts. A model using MATLAB has been developed and results are presented.

Robust wafer identification recognition based on asterisk-shape filter and high-low score comparison method.

PubMed

Hsu, Wei-Chih; Yu, Tsan-Ying; Chen, Kuan-Liang

2009-12-10

Wafer identifications (wafer ID) can be used to identify wafers from each other so that wafer processing can be traced easily. Wafer ID recognition is one of the problems of optical character recognition. The process to recognize wafer IDs is similar to that used in recognizing car license-plate characters. However, due to some unique characteristics, such as the irregular space between two characters and the unsuccessive strokes of wafer ID, it will not get a good result to recognize wafer ID by directly utilizing the approaches used in car license-plate character recognition. Wafer ID scratches are engraved by a laser scribe almost along the following four fixed directions: horizontal, vertical, plus 45 degrees , and minus 45 degrees orientations. The closer to the center line of a wafer ID scratch, the higher the gray level will be. These and other characteristics increase the difficulty to recognize the wafer ID. In this paper a wafer ID recognition scheme based on an asterisk-shape filter and a high-low score comparison method is proposed to cope with the serious influence of uneven luminance and make recognition more efficiently. Our proposed approach consists of some processing stages. Especially in the final recognition stage, a template-matching method combined with stroke analysis is used as a recognizing scheme. This is because wafer IDs are composed of Semiconductor Equipment and Materials International (SEMI) standard Arabic numbers and English alphabets, and thus the template ID images are easy to obtain. Furthermore, compared with the approach that requires prior training, such as a support vector machine, which often needs a large amount of training image samples, no prior training is required for our approach. The testing results show that our proposed scheme can efficiently and correctly segment out and recognize the wafer ID with high performance.

Method for traffic-sign detection within a picture by color identification and external shape recognition

NASA Astrophysics Data System (ADS)

Falcoff, Daniel E.; Canali, Luis R.

1999-08-01

This work present one method aimed to individualization and recognition of vial signs in route and city. It is based fundamentally on the identification by means of color and form of the vial sing, located in the border of the route or street in city, and then recognition. To do so the obtained RGB image is processed, carrying out diverse filtrates in the sequence of input image, or intensifying the colors of the same ones otherwise, recognizing their silhouette and then segmenting the sign and comparing the symbology of them with the previously stored and classified database.

Spline curve matching with sparse knot sets: applications to deformable shape detection and recognition

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Neil A. Clark; Philip A. Araman

2003-01-01

Splines can be used to approximate noisy data with a few control points. This paper presents a new curve matching method for deformable shapes using two-dimensional splines. In contrast to the residual error criterion, which is based on relative locations of corresponding knot points such that is reliable primarily for dense point sets, we use deformation energy of...

Automatic Recognition of Road Signs

NASA Astrophysics Data System (ADS)

Inoue, Yasuo; Kohashi, Yuuichirou; Ishikawa, Naoto; Nakajima, Masato

2002-11-01

The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver"s carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver"s safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver"s carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.

Designing of MIP based QCM sensor having thymine recognition sites based on biomimicking DNA approach.

PubMed

Diltemiz, S Emir; Hür, D; Ersöz, A; Denizli, A; Say, R

2009-11-15

Quartz crystal microbalance (QCM) sensors coated with molecular imprinted polymers (MIP) have been developed for the determination of thymine. In this method, methacryloylamidoadenine (MA-Ade) have used as a new monomer and thymine template for inspiration of DNA nucleobases interaction. The thymine can be simultaneously hydrogen binding to MA-Ade and fit into the shape-selective cavities. Thus, the interaction between nucleobases has an effect on the binding ability of the QCM sensors. The binding affinity of the thymine imprinted sensors has investigated by using the Langmuir isotherm. The thymine imprinted QCM electrodes have shown homogeneous binding sites for thymine (K(a): 1.0 x 10(5)M(-1)) while heterogeneous binding sites for uracil. On the other hand, recognition selectivity of the QCM sensor based on thymine imprinted polymer toward to uracil, ssDNA and ssRNA has been reported in this work.

Traffic Sign Detection Based on Biologically Visual Mechanism

NASA Astrophysics Data System (ADS)

Hu, X.; Zhu, X.; Li, D.

2012-07-01

TSR (Traffic sign recognition) is an important problem in ITS (intelligent traffic system), which is being paid more and more attention for realizing drivers assisting system and unmanned vehicle etc. TSR consists of two steps: detection and recognition, and this paper describe a new traffic sign detection method. The design principle of the traffic sign is comply with the visual attention mechanism of human, so we propose a method using visual attention mechanism to detect traffic sign ,which is reasonable. In our method, the whole scene will firstly be analyzed by visual attention model to acquire the area where traffic signs might be placed. And then, these candidate areas will be analyzed according to the shape characteristics of the traffic sign to detect traffic signs. In traffic sign detection experiments, the result shows the proposed method is effectively and robust than other existing saliency detection method.

[Synthesis and Study on Adsorption Property of Congo Red Molecularly Imprinted Polymer Nanospheres].

PubMed

Chang, Zi-qiang; Chen, Fu-bin; Zhang, Yu; Shi, Zuo-long; Yang, Chun-yan; Zhang, Zhu-jun

2015-07-01

Molecularly imprinted polymer nanospheres (MIP) were prepared with Congo red as the template, methacrylic acid (MAA) as a functional monomer, ethylene glycol dimethacrylate (EGDMA) as the cross linker, azodiisobutyronitrile (AIBN) as an initiator, and acetonitrile as the porogen by precipitation polymerization. The morphology of MIP was characterized by SEM and TEM which showed that the diameter of MIP was nanometer grade (90 nm) and the shape was homogeneous. The specific surface area and pore volumes of MIP and NIP were examined through Brunauer-Emett-Teller method of nitrogen adsorption experiments. Then, the adsorption and selective recognition ability of MIPs were evaluated using the equilibrium rebinding experiments. The results indicated that the prepared MIP showed a good selectivity recognition ability to its template. It concluded that MIP could be employed as an effective material for removing Congo red from waste water.

Effects of WDRC release time and number of channels on output SNR and speech recognition

PubMed Central

Alexander, Joshua M.; Masterson, Katie

2014-01-01

Objectives The purpose of this study was to investigate the joint effects that wide dynamic range compression (WDRC) release time (RT) and number of channels have on recognition of sentences in the presence of steady and modulated maskers at different signal-to-noise ratios (SNRs). How the different combinations of WDRC parameters affect output SNR and the role this plays in the observed findings was also investigated. Design Twenty-four listeners with mild to moderate sensorineural hearing loss identified sentences mixed with steady or modulated maskers at 3 SNRs (−5, 0, +5 dB) that had been processed using a hearing aid simulator with 6 combinations of RT (40 and 640 ms) and number of channels (4, 8, and 16). Compression parameters were set using the Desired Sensation Level v5.0a prescriptive fitting method. For each condition, amplified speech and masker levels and the resultant long-term output SNR were measured. Results Speech recognition with WDRC depended on the combination of RT and number of channels, with the greatest effects observed at 0 dB input SNR, in which mean speech recognition scores varied by 10–12% across WDRC manipulations. Overall, effect sizes were generally small. Across both masker types and the three SNRs tested, the best speech recognition was obtained with 8 channels, regardless of RT. Increased speech levels, which favor audibility, were associated with the short RT and with an increase in the number of channels. These same conditions also increased masker levels by an even greater amount, for a net decrease in the long-term output SNR. Changes in long-term SNR across WDRC conditions were found to be strongly associated with changes in the temporal envelope shape as quantified by the Envelope Difference Index, however, neither of these factors fully explained the observed differences in speech recognition. Conclusions A primary finding of this study was that the number of channels had a modest effect when analyzed at each level of RT, with results suggesting that selecting 8 channels for a given RT might be the safest choice. Effects were smaller for RT, with results suggesting that short RT was slightly better when only 4 channels were used and that long RT was better when 16 channels were used. Individual differences in how listeners were influenced by audibility, output SNR, temporal distortion, and spectral distortion may have contributed to the size of the effects found in this study. Because only general suppositions could made for how each of these factors may have influenced the overall results of this study, future research would benefit from exploring the predictive value of these and other factors in selecting the processing parameters that maximize speech recognition for individuals. PMID:25470368

Can You See Me Now Visualizing Battlefield Facial Recognition Technology in 2035

DTIC Science & Technology

2010-04-01

County Sheriff’s Department, use certain measurements such as the distance between eyes, the length of the nose, or the shape of the ears. 8 However...captures multiple frames of video and composites them into an appropriately high-resolution image that can be processed by the facial recognition software...stream of data. High resolution video systems, such as those described below will be able to capture orders of magnitude more data in one video frame

Implicit Shape Models for Object Detection in 3d Point Clouds

NASA Astrophysics Data System (ADS)

Velizhev, A.; Shapovalov, R.; Schindler, K.

2012-07-01

We present a method for automatic object localization and recognition in 3D point clouds representing outdoor urban scenes. The method is based on the implicit shape models (ISM) framework, which recognizes objects by voting for their center locations. It requires only few training examples per class, which is an important property for practical use. We also introduce and evaluate an improved version of the spin image descriptor, more robust to point density variation and uncertainty in normal direction estimation. Our experiments reveal a significant impact of these modifications on the recognition performance. We compare our results against the state-of-the-art method and get significant improvement in both precision and recall on the Ohio dataset, consisting of combined aerial and terrestrial LiDAR scans of 150,000 m2 of urban area in total.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner.

PubMed

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-07-20

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner

PubMed Central

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-01-01

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation. PMID:27447640

Two-dimensional shape recognition using sparse distributed memory

NASA Technical Reports Server (NTRS)

Kanerva, Pentti; Olshausen, Bruno

1990-01-01

Researchers propose a method for recognizing two-dimensional shapes (hand-drawn characters, for example) with an associative memory. The method consists of two stages: first, the image is preprocessed to extract tangents to the contour of the shape; second, the set of tangents is converted to a long bit string for recognition with sparse distributed memory (SDM). SDM provides a simple, massively parallel architecture for an associative memory. Long bit vectors (256 to 1000 bits, for example) serve as both data and addresses to the memory, and patterns are grouped or classified according to similarity in Hamming distance. At the moment, tangents are extracted in a simple manner by progressively blurring the image and then using a Canny-type edge detector (Canny, 1986) to find edges at each stage of blurring. This results in a grid of tangents. While the technique used for obtaining the tangents is at present rather ad hoc, researchers plan to adopt an existing framework for extracting edge orientation information over a variety of resolutions, such as suggested by Watson (1987, 1983), Marr and Hildreth (1980), or Canny (1986).

Social power and recognition of emotional prosody: High power is associated with lower recognition accuracy than low power.

PubMed

Uskul, Ayse K; Paulmann, Silke; Weick, Mario

2016-02-01

Listeners have to pay close attention to a speaker's tone of voice (prosody) during daily conversations. This is particularly important when trying to infer the emotional state of the speaker. Although a growing body of research has explored how emotions are processed from speech in general, little is known about how psychosocial factors such as social power can shape the perception of vocal emotional attributes. Thus, the present studies explored how social power affects emotional prosody recognition. In a correlational study (Study 1) and an experimental study (Study 2), we show that high power is associated with lower accuracy in emotional prosody recognition than low power. These results, for the first time, suggest that individuals experiencing high or low power perceive emotional tone of voice differently. (c) 2016 APA, all rights reserved).

3D abnormal behavior recognition in power generation

NASA Astrophysics Data System (ADS)

Wei, Zhenhua; Li, Xuesen; Su, Jie; Lin, Jie

2011-06-01

So far most research of human behavior recognition focus on simple individual behavior, such as wave, crouch, jump and bend. This paper will focus on abnormal behavior with objects carrying in power generation. Such as using mobile communication device in main control room, taking helmet off during working and lying down in high place. Taking account of the color and shape are fixed, we adopted edge detecting by color tracking to recognize object in worker. This paper introduces a method, which using geometric character of skeleton and its angle to express sequence of three-dimensional human behavior data. Then adopting Semi-join critical step Hidden Markov Model, weighing probability of critical steps' output to reduce the computational complexity. Training model for every behavior, mean while select some skeleton frames from 3D behavior sample to form a critical step set. This set is a bridge linking 2D observation behavior with 3D human joints feature. The 3D reconstruction is not required during the 2D behavior recognition phase. In the beginning of recognition progress, finding the best match for every frame of 2D observed sample in 3D skeleton set. After that, 2D observed skeleton frames sample will be identified as a specifically 3D behavior by behavior-classifier. The effectiveness of the proposed algorithm is demonstrated with experiments in similar power generation environment.

A new accurate pill recognition system using imprint information

NASA Astrophysics Data System (ADS)

Chen, Zhiyuan; Kamata, Sei-ichiro

2013-12-01

Great achievements in modern medicine benefit human beings. Also, it has brought about an explosive growth of pharmaceuticals that current in the market. In daily life, pharmaceuticals sometimes confuse people when they are found unlabeled. In this paper, we propose an automatic pill recognition technique to solve this problem. It functions mainly based on the imprint feature of the pills, which is extracted by proposed MSWT (modified stroke width transform) and described by WSC (weighted shape context). Experiments show that our proposed pill recognition method can reach an accurate rate up to 92.03% within top 5 ranks when trying to classify more than 10 thousand query pill images into around 2000 categories.

Off-lexicon online Arabic handwriting recognition using neural network

NASA Astrophysics Data System (ADS)

Yahia, Hamdi; Chaabouni, Aymen; Boubaker, Houcine; Alimi, Adel M.

2017-03-01

This paper highlights a new method for online Arabic handwriting recognition based on graphemes segmentation. The main contribution of our work is to explore the utility of Beta-elliptic model in segmentation and features extraction for online handwriting recognition. Indeed, our method consists in decomposing the input signal into continuous part called graphemes based on Beta-Elliptical model, and classify them according to their position in the pseudo-word. The segmented graphemes are then described by the combination of geometric features and trajectory shape modeling. The efficiency of the considered features has been evaluated using feed forward neural network classifier. Experimental results using the benchmarking ADAB Database show the performance of the proposed method.

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Arguments Against a Configural Processing Account of Familiar Face Recognition.

PubMed

Burton, A Mike; Schweinberger, Stefan R; Jenkins, Rob; Kaufmann, Jürgen M

2015-07-01

Face recognition is a remarkable human ability, which underlies a great deal of people's social behavior. Individuals can recognize family members, friends, and acquaintances over a very large range of conditions, and yet the processes by which they do this remain poorly understood, despite decades of research. Although a detailed understanding remains elusive, face recognition is widely thought to rely on configural processing, specifically an analysis of spatial relations between facial features (so-called second-order configurations). In this article, we challenge this traditional view, raising four problems: (1) configural theories are underspecified; (2) large configural changes leave recognition unharmed; (3) recognition is harmed by nonconfigural changes; and (4) in separate analyses of face shape and face texture, identification tends to be dominated by texture. We review evidence from a variety of sources and suggest that failure to acknowledge the impact of familiarity on facial representations may have led to an overgeneralization of the configural account. We argue instead that second-order configural information is remarkably unimportant for familiar face recognition. © The Author(s) 2015.

Line-based logo recognition through a web-camera

NASA Astrophysics Data System (ADS)

Chen, Xiaolu; Wang, Yangsheng; Feng, Xuetao

2007-11-01

Logo recognition has gained much development in the document retrieval and shape analysis domain. As human computer interaction becomes more and more popular, the logo recognition through a web-camera is a promising technology in view of application. But for practical application, the study of logo recognition in real scene is much more difficult than the work in clear scene. To cope with the need, we make some improvements on conventional method. First, moment information is used to calculate the test image's orientation angle, which is used to normalize the test image. Second, the main structure of the test image, which is represented by lines patterns, is acquired and modified Hausdorff distance is employed to match the image and each of the existing templates. The proposed method, which is invariant to scale and rotation, gives good result and can work at real-time. The main contribution of this paper is that some improvements are introduced into the exiting recognition framework which performs much better than the original one. Besides, we have built a highly successful logo recognition system using our improved method.

Tactile Recognition and Localization Using Object Models: The Case of Polyhedra on a Plane.

DTIC Science & Technology

1983-03-01

poor force resolution, but high spatial resolution. We feel that the viability of this recognition approach has important implications on the design of...of the touched object: 1. Surface point - On the basis of sensor readings, some points on the sensor can be identified as being in contact with...the sensor’s shape and location in space are known, one can determine the position of some point on the touched object, to within some uncertainty

Design of relative motion and attitude profiles for three-dimensional resident space object imaging with a laser rangefinder

NASA Astrophysics Data System (ADS)

Nayak, M.; Beck, J.; Udrea, B.

This paper focuses on the aerospace application of a single beam laser rangefinder (LRF) for 3D imaging, shape detection, and reconstruction in the context of a space-based space situational awareness (SSA) mission scenario. The primary limitation to 3D imaging from LRF point clouds is the one-dimensional nature of the single beam measurements. A method that combines relative orbital motion and scanning attitude motion to generate point clouds has been developed and the design and characterization of multiple relative motion and attitude maneuver profiles are presented. The target resident space object (RSO) has the shape of a generic telecommunications satellite. The shape and attitude of the RSO are unknown to the chaser satellite however, it is assumed that the RSO is un-cooperative and has fixed inertial pointing. All sensors in the metrology chain are assumed ideal. A previous study by the authors used pure Keplerian motion to perform a similar 3D imaging mission at an asteroid. A new baseline for proximity operations maneuvers for LRF scanning, based on a waypoint adaptation of the Hill-Clohessy-Wiltshire (HCW) equations is examined. Propellant expenditure for each waypoint profile is discussed and combinations of relative motion and attitude maneuvers that minimize the propellant used to achieve a minimum required point cloud density are studied. Both LRF strike-point coverage and point cloud density are maximized; the capability for 3D shape registration and reconstruction from point clouds generated with a single beam LRF without catalog comparison is proven. Next, a method of using edge detection algorithms to process a point cloud into a 3D modeled image containing reconstructed shapes is presented. Weighted accuracy of edge reconstruction with respect to the true model is used to calculate a qualitative “ metric” that evaluates effectiveness of coverage. Both edge recognition algorithms and the metric are independent of point cloud densit- , therefore they are utilized to compare the quality of point clouds generated by various attitude and waypoint command profiles. The RSO model incorporates diverse irregular protruding shapes, such as open sensor covers, instrument pods and solar arrays, to test the limits of the algorithms. This analysis is used to mathematically prove that point clouds generated by a single-beam LRF can achieve sufficient edge recognition accuracy for SSA applications, with meaningful shape information extractable even from sparse point clouds. For all command profiles, reconstruction of RSO shapes from the point clouds generated with the proposed method are compared to the truth model and conclusions are drawn regarding their fidelity.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

PubMed

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual recognition. Copyright © 2010 Elsevier Srl. All rights reserved.

End-to-end system of license plate localization and recognition

NASA Astrophysics Data System (ADS)

Zhu, Siyu; Dianat, Sohail; Mestha, Lalit K.

2015-03-01

An end-to-end license plate recognition system is proposed. It is composed of preprocessing, detection, segmentation, and character recognition to find and recognize plates from camera-based still images. The system utilizes connected component (CC) properties to quickly extract the license plate region. A two-stage CC filtering is utilized to address both shape and spatial relationship information to produce high precision and to recall values for detection. Floating peak and valleys of projection profiles are used to cut the license plates into individual characters. A turning function-based method is proposed to quickly and accurately recognize each character. It is further accelerated using curvature histogram-based support vector machine. The INFTY dataset is used to train the recognition system, and MediaLab license plate dataset is used for testing. The proposed system achieved 89.45% F-measure for detection and 87.33% accuracy for overall recognition rate which is comparable to current state-of-the-art systems.

Word recognition using a lexicon constrained by first/last character decisions

NASA Astrophysics Data System (ADS)

Zhao, Sheila X.; Srihari, Sargur N.

1995-03-01

In lexicon based recognition of machine-printed word images, the size of the lexicon can be quite extensive. The recognition performance is closely related to the size of the lexicon. Recognition performance drops quickly when lexicon size increases. Here, we present an algorithm to improve the word recognition performance by reducing the size of the given lexicon. The algorithm utilizes the information provided by the first and last characters of a word to reduce the size of the given lexicon. Given a word image and a lexicon that contains the word in the image, the first and last characters are segmented and then recognized by a character classifier. The possible candidates based on the results given by the classifier are selected, which give us the sub-lexicon. Then a word shape analysis algorithm is applied to produce the final ranking of the given lexicon. The algorithm was tested on a set of machine- printed gray-scale word images which includes a wide range of print types and qualities.

Illumination-invariant hand gesture recognition

NASA Astrophysics Data System (ADS)

Mendoza-Morales, América I.; Miramontes-Jaramillo, Daniel; Kober, Vitaly

2015-09-01

In recent years, human-computer interaction (HCI) has received a lot of interest in industry and science because it provides new ways to interact with modern devices through voice, body, and facial/hand gestures. The application range of the HCI is from easy control of home appliances to entertainment. Hand gesture recognition is a particularly interesting problem because the shape and movement of hands usually are complex and flexible to be able to codify many different signs. In this work we propose a three step algorithm: first, detection of hands in the current frame is carried out; second, hand tracking across the video sequence is performed; finally, robust recognition of gestures across subsequent frames is made. Recognition rate highly depends on non-uniform illumination of the scene and occlusion of hands. In order to overcome these issues we use two Microsoft Kinect devices utilizing combined information from RGB and infrared sensors. The algorithm performance is tested in terms of recognition rate and processing time.

Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.

PubMed

Venkataraman, Vinay; Turaga, Pavan

2016-12-01

This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

Different effect of hydrogelation on anti-fouling and circulation properties of dextran–iron oxide nanoparticles

PubMed Central

Karmali, Priya Prakash; Chao, Ying; Park, Ji-Ho (Joe); Sailor, Michael J.; Ruoslahti, Erkki; Esener, Sadik C.; Simberg, Dmitri

2012-01-01

Premature recognition and clearance of nanoparticulate imaging and therapeutic agents by macrophages in the tissues can dramatically reduce both the nanoparticle half-life and delivery to the diseased tissue. Grafting nanoparticles with hydrogels prevents nanoparticulate recognition by liver and spleen macrophages and greatly prolongs circulation times in vivo. Understanding the mechanisms by which hydrogels achieve this “stealth” effect has implications for the design of long-circulating nanoparticles. Thus, the role of plasma protein absorption in the hydrogel effect is not yet understood. Short-circulating dextran-coated iron oxide nanoparticles could be converted into stealth hydrogel nanoparticles by crosslinking with 1-chloro-2,3-epoxypropane. We show that hydrogelation did not affect the size, shape and zeta potential, but completely prevented the recognition and clearance by liver macrophages in vivo. Hydrogelation decreased the number of hydroxyl groups on the nanoparticle surface and reduced the binding of the anti-dextran antibody. At the same time, hydrogelation did not reduce the absorption of cationic proteins on the nanoparticle surface. Specifically, there was no effect on the binding of kininogen, histidine-rich glycoprotein, and protamine sulfate to the anionic nanoparticle surface. In addition, hydrogelation did not prevent activation of plasma kallikrein on the metal oxide surface. These data suggest that: (a) a stealth hydrogel coating does not mask charge interactions with iron oxide surface and (b) the total blockade of plasma protein absorption is not required for maintaining iron oxide nanoparticles’ long-circulating stealth properties. These data illustrate a novel, clinically promising property of long-circulating stealth nanoparticles. PMID:22243419

Robust traffic sign detection using fuzzy shape recognizer

NASA Astrophysics Data System (ADS)

Li, Lunbo; Li, Jun; Sun, Jianhong

2009-10-01

A novel fuzzy approach for the detection of traffic signs in natural environments is presented. More than 3000 road images were collected under different weather conditions by a digital camera, and used for testing this approach. Every RGB image was converted into HSV colour space, and segmented by the hue and saturation thresholds. A symmetrical detector was used to extract the local features of the regions of interest (ROI), and the shape of ROI was determined by a fuzzy shape recognizer which invoked a set of fuzzy rules. The experimental results show that the proposed algorithm is translation, rotation and scaling invariant, and gives reliable shape recognition in complex traffic scenes where clustering and partial occlusion normally occur.

Grouping in object recognition: the role of a Gestalt law in letter identification.

PubMed

Pelli, Denis G; Majaj, Najib J; Raizman, Noah; Christian, Christopher J; Kim, Edward; Palomares, Melanie C

2009-02-01

The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws "prescribe for us what we are to recognize 'as one thing'" (Kohler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and "snakes in the grass" is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, "wiggle", to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping.

Grouping in object recognition: The role of a Gestalt law in letter identification

PubMed Central

Pelli, Denis G.; Majaj, Najib J.; Raizman, Noah; Christian, Christopher J.; Kim, Edward; Palomares, Melanie C.

2009-01-01

The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws “prescribe for us what we are to recognize ‘as one thing’” (Köhler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and “snakes in the grass” is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, “wiggle”, to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping. PMID:19424881

The evolution of immunity in relation to colonization and migration.

PubMed

O'Connor, Emily A; Cornwallis, Charlie K; Hasselquist, Dennis; Nilsson, Jan-Åke; Westerdahl, Helena

2018-05-01

Colonization and migration have a crucial effect on patterns of biodiversity, with disease predicted to play an important role in these processes. However, evidence of the effect of pathogens on broad patterns of colonization and migration is limited. Here, using phylogenetic analyses of 1,311 species of Afro-Palaearctic songbirds, we show that colonization events from regions of high (sub-Saharan Africa) to low (the Palaearctic) pathogen diversity were up to 20 times more frequent than the reverse, and that migration has evolved 3 times more frequently from African- as opposed to Palaearctic-resident species. We also found that resident species that colonized the Palaearctic from Africa, as well as African species that evolved long-distance migration to breed in the Palaearctic, have reduced diversity of key immune genes associated with pathogen recognition (major histocompatibility complex class I). These results suggest that changes in the pathogen community that occur during colonization and migration shape the evolution of the immune system, potentially by adjusting the trade-off between the benefits of extensive pathogen recognition and the costs of immunopathology that result from high major histocompatibility complex class I diversity.

Learning the spherical harmonic features for 3-D face recognition.

PubMed

Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

2013-03-01

In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method.

Square bananas, blue horses: the relative weight of shape and color in concept recognition and representation

PubMed Central

Scorolli, Claudia; Borghi, Anna M.

2015-01-01

The present study investigates the role that shape and color play in the representation of animate (i.e., animals) and inanimate manipulable entities (i.e., fruits), and how the importance of these features is modulated by different tasks. Across three experiments participants were shown either images of entities (e.g., a sheep or a pineapple) or images of the same entities modified in color (e.g., a blue pineapple) or in shape (e.g., an elongated pineapple). In Experiment 1 we asked participants to categorize the entities as fruit or animal. Results showed that with animals color does not matter, while shape modifications determined a deterioration of the performance – stronger for fruit than for animals. To better understand our findings, in Experiments 2 we asked participants to judge if entities were graspable (manipulation evaluation task). Participants were faster with manipulable entities (fruit) than with animals; moreover alterations in shape affected the response latencies more for animals than for fruit. In Experiment 3 (motion evaluation task), we replicated the disadvantage for shape-altered animals, while with fruits shape and color modifications produced no effect. By contrasting shape- and color- alterations the present findings provide information on shape/color relative weight, suggesting that the action based property of shape is more crucial than color for fruit categorization, while with animals it is critical for both manipulation and motion tasks. This contextual dependency is further revealed by explicit judgments on similarity – between the altered entities and the prototypical ones – provided after the different tasks. These results extend current literature on affordances and biofunctionally embodied understanding, revealing the relative robustness of biofunctional activity compared to intellectual one. PMID:26500593

Three RNA recognition motifs participate in RNA recognition and structural organization by the pro-apoptotic factor TIA-1

PubMed Central

Bauer, William J.; Heath, Jason; Jenkins, Jermaine L.; Kielkopf, Clara L.

2012-01-01

T-cell intracellular antigen-1 (TIA-1) regulates developmental and stress-responsive pathways through distinct activities at the levels of alternative pre-mRNA splicing and mRNA translation. The TIA-1 polypeptide contains three RNA recognition motifs (RRMs). The central RRM2 and C-terminal RRM3 associate with cellular mRNAs. The N-terminal RRM1 enhances interactions of a C-terminal Q-rich domain of TIA-1 with the U1-C splicing factor, despite linear separation of the domains in the TIA-1 sequence. Given the expanded functional repertoire of the RRM family, it was unknown whether TIA-1 RRM1 contributes to RNA binding as well as documented protein interactions. To address this question, we used isothermal titration calorimetry and small-angle X-ray scattering (SAXS) to dissect the roles of the TIA-1 RRMs in RNA recognition. Notably, the fas RNA exhibited two binding sites with indistinguishable affinities for TIA-1. Analyses of TIA-1 variants established that RRM1 was dispensable for binding AU-rich fas sites, yet all three RRMs were required to bind a polyU RNA with high affinity. SAXS analyses demonstrated a `V' shape for a TIA-1 construct comprising the three RRMs, and revealed that its dimensions became more compact in the RNA-bound state. The sequence-selective involvement of TIA-1 RRM1 in RNA recognition suggests a possible role for RNA sequences in regulating the distinct functions of TIA-1. Further implications for U1-C recruitment by the adjacent TIA-1 binding sites of the fas pre-mRNA and the bent TIA-1 shape, which organizes the N- and C-termini on the same side of the protein, are discussed. PMID:22154808

Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

NASA Astrophysics Data System (ADS)

Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

2014-12-01

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

How landmark suitability shapes recognition memory signals for objects in the medial temporal lobes.

PubMed

Martin, Chris B; Sullivan, Jacqueline A; Wright, Jessey; Köhler, Stefan

2018-02-01

A role of perirhinal cortex (PrC) in recognition memory for objects has been well established. Contributions of parahippocampal cortex (PhC) to this function, while documented, remain less well understood. Here, we used fMRI to examine whether the organization of item-based recognition memory signals across these two structures is shaped by object category, independent of any difference in representing episodic context. Guided by research suggesting that PhC plays a critical role in processing landmarks, we focused on three categories of objects that differ from each other in their landmark suitability as confirmed with behavioral ratings (buildings > trees > aircraft). Participants made item-based recognition-memory decisions for novel and previously studied objects from these categories, which were matched in accuracy. Multi-voxel pattern classification revealed category-specific item-recognition memory signals along the long axis of PrC and PhC, with no sharp functional boundaries between these structures. Memory signals for buildings were observed in the mid to posterior extent of PhC, signals for trees in anterior to posterior segments of PhC, and signals for aircraft in mid to posterior aspects of PrC and the anterior extent of PhC. Notably, item-based memory signals for the category with highest landmark suitability ratings were observed only in those posterior segments of PhC that also allowed for classification of landmark suitability of objects when memory status was held constant. These findings provide new evidence in support of the notion that item-based memory signals for objects are not limited to PrC, and that the organization of these signals along the longitudinal axis that crosses PrC and PhC can be captured with reference to landmark suitability. Copyright © 2017 Elsevier Inc. All rights reserved.

Object Recognition and Localization: The Role of Tactile Sensors

PubMed Central

Aggarwal, Achint; Kirchner, Frank

2014-01-01

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments. PMID:24553087

It Takes Two–Skilled Recognition of Objects Engages Lateral Areas in Both Hemispheres

PubMed Central

Bilalić, Merim; Kiesel, Andrea; Pohl, Carsten; Erb, Michael; Grodd, Wolfgang

2011-01-01

Our object recognition abilities, a direct product of our experience with objects, are fine-tuned to perfection. Left temporal and lateral areas along the dorsal, action related stream, as well as left infero-temporal areas along the ventral, object related stream are engaged in object recognition. Here we show that expertise modulates the activity of dorsal areas in the recognition of man-made objects with clearly specified functions. Expert chess players were faster than chess novices in identifying chess objects and their functional relations. Experts' advantage was domain-specific as there were no differences between groups in a control task featuring geometrical shapes. The pattern of eye movements supported the notion that experts' extensive knowledge about domain objects and their functions enabled superior recognition even when experts were not directly fixating the objects of interest. Functional magnetic resonance imaging (fMRI) related exclusively the areas along the dorsal stream to chess specific object recognition. Besides the commonly involved left temporal and parietal lateral brain areas, we found that only in experts homologous areas on the right hemisphere were also engaged in chess specific object recognition. Based on these results, we discuss whether skilled object recognition does not only involve a more efficient version of the processes found in non-skilled recognition, but also qualitatively different cognitive processes which engage additional brain areas. PMID:21283683

The Prototype of Indicators of a Responsive Partner Shapes Information Processing: A False Recognition Study.

PubMed

Turan, Bulent

2016-01-01

When judging whether a relationship partner can be counted on to "be there" when needed, people may draw upon knowledge structures to process relevant information. We examined one such knowledge structure using the prototype methodology: indicators of a partner who is likely to be there when needed. In the first study (N = 91), the structure, content, and reliability of the prototype of indicators were examined. Then, using a false recognition study (N = 77), we demonstrated that once activated, the prototype of indicators of a partner who is likely to be there when needed affects information processing. Thus, the prototype of indicators may shape how people process support-relevant information in everyday life, affecting relationship outcomes. Using this knowledge structure may help a person process relevant information quickly and with cognitive economy. However, it may also lead to biases in judgments in certain situations.

Unsupervised categorization method of graphemes on handwritten manuscripts: application to style recognition

NASA Astrophysics Data System (ADS)

Daher, H.; Gaceb, D.; Eglin, V.; Bres, S.; Vincent, N.

2012-01-01

We present in this paper a feature selection and weighting method for medieval handwriting images that relies on codebooks of shapes of small strokes of characters (graphemes that are issued from the decomposition of manuscripts). These codebooks are important to simplify the automation of the analysis, the manuscripts transcription and the recognition of styles or writers. Our approach provides a precise features weighting by genetic algorithms and a highperformance methodology for the categorization of the shapes of graphemes by using graph coloring into codebooks which are applied in turn on CBIR (Content Based Image Retrieval) in a mixed handwriting database containing different pages from different writers, periods of the history and quality. We show how the coupling of these two mechanisms 'features weighting - graphemes classification' can offer a better separation of the forms to be categorized by exploiting their grapho-morphological, their density and their significant orientations particularities.

Interspecific comparison of traffic noise effects on dove coo transmission in urban environments.

PubMed

Shieh, Bao-Sen; Liang, Shih-Hsiung; Chiu, Yuh-Wen; Lin, Szu-Ying

2016-08-31

Most previous studies concerning avian adaptation to anthropogenic noise have focused on songbirds, but few have focused on non-songbirds commonly found in urban environments such as doves. We conducted field playback-recording experiments on the perch-coos of five dove species, including four native Taiwan species (the spotted dove, Spilopelia chinensis, the oriental turtle-dove, Streptopelia orientalis, the red collared-dove, Streptopelia tranquebarica, and the emerald dove, Chalcophaps indica) and one species not native to Taiwan (the zebra dove, Geopelia striata) to evaluate the detection and recognition of dove coos in habitats with differing levels of traffic noise. Our results suggest that traffic noise has selected dominant urban species such as the spotted dove to temporally and spatially adjust cooing to reduce the masking effects of traffic noise and rare urban species such as the emerald dove to avoid areas of high traffic noise. Additionally, although the zebra dove had the highest coo frequency among the study species, its coos showed the highest detection value but not the highest recognition value. We conclude that traffic noise is an important factor in shaping the distribution of rare and dominant dove species in urban environments through its significant effects on coo transmission.

Interspecific comparison of traffic noise effects on dove coo transmission in urban environments

NASA Astrophysics Data System (ADS)

Shieh, Bao-Sen; Liang, Shih-Hsiung; Chiu, Yuh-Wen; Lin, Szu-Ying

2016-08-01

Most previous studies concerning avian adaptation to anthropogenic noise have focused on songbirds, but few have focused on non-songbirds commonly found in urban environments such as doves. We conducted field playback-recording experiments on the perch-coos of five dove species, including four native Taiwan species (the spotted dove, Spilopelia chinensis, the oriental turtle-dove, Streptopelia orientalis, the red collared-dove, Streptopelia tranquebarica, and the emerald dove, Chalcophaps indica) and one species not native to Taiwan (the zebra dove, Geopelia striata) to evaluate the detection and recognition of dove coos in habitats with differing levels of traffic noise. Our results suggest that traffic noise has selected dominant urban species such as the spotted dove to temporally and spatially adjust cooing to reduce the masking effects of traffic noise and rare urban species such as the emerald dove to avoid areas of high traffic noise. Additionally, although the zebra dove had the highest coo frequency among the study species, its coos showed the highest detection value but not the highest recognition value. We conclude that traffic noise is an important factor in shaping the distribution of rare and dominant dove species in urban environments through its significant effects on coo transmission.

The mind of the mnemonists: an MEG and neuropsychological study of autistic memory savants.

PubMed

Neumann, Nicola; Dubischar-Krivec, Anna M; Braun, Christoph; Löw, Andreas; Poustka, Fritz; Bölte, Sven; Birbaumer, Niels

2010-12-20

About 10% of autistic individuals exhibit some form of islets of abilities in the face of serious intellectual or mental disability ("savant syndrome"). The aim of this study was to investigate brain mechanisms in a sample of autistic subjects with outstanding memory. We investigated seven mnemonist savants with high-functioning autism spectrum disorder and seven matched controls with 151-channel whole-head magnetencephalography in a continuous old-new paradigm. They were presented with 300 pseudowords and 300 shapes and had to indicate by button press, whether the presented stimulus had been shown before. Unexpectedly, mnemonist savants did not perform better than controls, but were outperformed in the recognition of pseudowords. Accordingly, event-related magnetic fields elicited by pseudowords showed widespread old-new effects in controls, but not in savants. A source analysis of its early components revealed right occipital activation in savants, but left parietal activation in controls. This might be related to a visual processing style in mnemonist savants that proved to be inefficient in this task. During the possibly familiarity-based recognition of shapes, there were earlier and more widespread bilateral old-new effects in mnemonist savants, what might reflect their experience with figural material. In a neuropsychological test battery, mnemonist savants performed comparably to autistic people without special memory skills. However, a different factor structure of these tests pointed to a different organization of memory in mnemonist savants compared to controls that is characterized by its relative independence of general intelligence. Copyright 2010 Elsevier B.V. All rights reserved.

Risk communication and radiological/nuclear terrorism: a strategic view.

PubMed

Becker, Steven M

2011-11-01

It is now widely recognized that effective communication is a crucial element in radiological/nuclear terrorism preparedness. Whereas in the past, communication and information issues were sometimes viewed as secondary in comparison with technical concerns, today the need to improve risk communication, public information, and emergency messaging is seen as a high priority. The process of improving radiological/nuclear terrorism risk communication can be conceptualized as occurring in four overlapping phases. The first phase involves the recognition that communication and information issues will be pivotal in shaping how a radiological/nuclear terrorism incident unfolds and in determining its outcome. This recognition has helped shape the second phase, in which various research initiatives have been undertaken to provide an empirical basis for improved communication. In the third and most recent phase, government agencies, professional organizations and others have worked to translate research findings into better messages and informational materials. Like the first and second phases, the third phase is still unfolding. The fourth phase in risk communication for radiological/nuclear terrorism-a mature phase-is only now just beginning. Central to this phase is a developing understanding that for radiological/nuclear terrorism risk communication to be fully effective, it must go beyond crafting better messages and materials (as essential as that may be). This emerging fourth phase seeks to anchor radiological/nuclear communication in a broader approach: one that actively engages and partners with the public. In this article, each of the four stages is discussed, and future directions for improving radiological/nuclear terrorism risk communication are explored.

Modeling of skin cancer dermatoscopy images

NASA Astrophysics Data System (ADS)

Iralieva, Malica B.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.

2018-04-01

An early identified cancer is more likely to effective respond to treatment and has a less expensive treatment as well. Dermatoscopy is one of general diagnostic techniques for skin cancer early detection that allows us in vivo evaluation of colors and microstructures on skin lesions. Digital phantoms with known properties are required during new instrument developing to compare sample's features with data from the instrument. An algorithm for image modeling of skin cancer is proposed in the paper. Steps of the algorithm include setting shape, texture generation, adding texture and normal skin background setting. The Gaussian represents the shape, and then the texture generation based on a fractal noise algorithm is responsible for spatial chromophores distributions, while the colormap applied to the values corresponds to spectral properties. Finally, a normal skin image simulated by mixed Monte Carlo method using a special online tool is added as a background. Varying of Asymmetry, Borders, Colors and Diameter settings is shown to be fully matched to the ABCD clinical recognition algorithm. The asymmetry is specified by setting different standard deviation values of Gaussian in different parts of image. The noise amplitude is increased to set the irregular borders score. Standard deviation is changed to determine size of the lesion. Colors are set by colormap changing. The algorithm for simulating different structural elements is required to match with others recognition algorithms.

A cultural side effect: learning to read interferes with identity processing of familiar objects

PubMed Central

Kolinsky, Régine; Fernandes, Tânia

2014-01-01

Based on the neuronal recycling hypothesis (Dehaene and Cohen, 2007), we examined whether reading acquisition has a cost for the recognition of non-linguistic visual materials. More specifically, we checked whether the ability to discriminate between mirror images, which develops through literacy acquisition, interferes with object identity judgments, and whether interference strength varies as a function of the nature of the non-linguistic material. To these aims we presented illiterate, late literate (who learned to read at adult age), and early literate adults with an orientation-independent, identity-based same-different comparison task in which they had to respond “same” to both physically identical and mirrored or plane-rotated images of pictures of familiar objects (Experiment 1) or of geometric shapes (Experiment 2). Interference from irrelevant orientation variations was stronger with plane rotations than with mirror images, and stronger with geometric shapes than with objects. Illiterates were the only participants almost immune to mirror variations, but only for familiar objects. Thus, the process of unlearning mirror-image generalization, necessary to acquire literacy in the Latin alphabet, has a cost for a basic function of the visual ventral object recognition stream, i.e., identification of familiar objects. This demonstrates that neural recycling is not just an adaptation to multi-use but a process of at least partial exaptation. PMID:25400605

Invariant visual object recognition and shape processing in rats

PubMed Central

Zoccolan, Davide

2015-01-01

Invariant visual object recognition is the ability to recognize visual objects despite the vastly different images that each object can project onto the retina during natural vision, depending on its position and size within the visual field, its orientation relative to the viewer, etc. Achieving invariant recognition represents such a formidable computational challenge that is often assumed to be a unique hallmark of primate vision. Historically, this has limited the invasive investigation of its neuronal underpinnings to monkey studies, in spite of the narrow range of experimental approaches that these animal models allow. Meanwhile, rodents have been largely neglected as models of object vision, because of the widespread belief that they are incapable of advanced visual processing. However, the powerful array of experimental tools that have been developed to dissect neuronal circuits in rodents has made these species very attractive to vision scientists too, promoting a new tide of studies that have started to systematically explore visual functions in rats and mice. Rats, in particular, have been the subjects of several behavioral studies, aimed at assessing how advanced object recognition and shape processing is in this species. Here, I review these recent investigations, as well as earlier studies of rat pattern vision, to provide an historical overview and a critical summary of the status of the knowledge about rat object vision. The picture emerging from this survey is very encouraging with regard to the possibility of using rats as complementary models to monkeys in the study of higher-level vision. PMID:25561421

Multi-scale Imaging of Cellular and Sub-cellular Structures using Scanning Probe Recognition Microscopy.

NASA Astrophysics Data System (ADS)

Chen, Q.; Rice, A. F.

2005-03-01

Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).

Chiral recognition and selection during the self-assembly process of protein-mimic macroanions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, Panchao; Zhang, Zhi-Ming; Lv, Hongjin

The research on chiral recognition and chiral selection is not only fundamental in resolving the puzzle of homochirality, but also instructive in chiral separation and stereoselective catalysis. Here we report the chiral recognition and chiral selection during the self-assembly process of two enantiomeric wheel-shaped macroanions, [Fe28(μ3-O)8(Tart)16(HCOO)24]20- (Tart=D- or L-tartaric acid tetra-anion). The enantiomers are observed to remain self-sorted and self-assemble into their individual assemblies in their racemic mixture solution. The addition of chiral co-anions can selectively suppress the self-assembly process of the enantiomeric macroanions, which is further used to separate the two enantiomers from their mixtures on the basis ofmore » the size difference between the monomers and the assemblies. We believe that delicate long-range electrostatic interactions could be responsible for such high-level chiral recognition and selection.« less

Facial soft biometric features for forensic face recognition.

PubMed

Tome, Pedro; Vera-Rodriguez, Ruben; Fierrez, Julian; Ortega-Garcia, Javier

2015-12-01

This paper proposes a functional feature-based approach useful for real forensic caseworks, based on the shape, orientation and size of facial traits, which can be considered as a soft biometric approach. The motivation of this work is to provide a set of facial features, which can be understood by non-experts such as judges and support the work of forensic examiners who, in practice, carry out a thorough manual comparison of face images paying special attention to the similarities and differences in shape and size of various facial traits. This new approach constitutes a tool that automatically converts a set of facial landmarks to a set of features (shape and size) corresponding to facial regions of forensic value. These features are furthermore evaluated in a population to generate statistics to support forensic examiners. The proposed features can also be used as additional information that can improve the performance of traditional face recognition systems. These features follow the forensic methodology and are obtained in a continuous and discrete manner from raw images. A statistical analysis is also carried out to study the stability, discrimination power and correlation of the proposed facial features on two realistic databases: MORPH and ATVS Forensic DB. Finally, the performance of both continuous and discrete features is analyzed using different similarity measures. Experimental results show high discrimination power and good recognition performance, especially for continuous features. A final fusion of the best systems configurations achieves rank 10 match results of 100% for ATVS database and 75% for MORPH database demonstrating the benefits of using this information in practice. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A contour-based shape descriptor for biomedical image classification and retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Contours, object blobs, and specific feature points are utilized to represent object shapes and extract shape descriptors that can then be used for object detection or image classification. In this research we develop a shape descriptor for biomedical image type (or, modality) classification. We adapt a feature extraction method used in optical character recognition (OCR) for character shape representation, and apply various image preprocessing methods to successfully adapt the method to our application. The proposed shape descriptor is applied to radiology images (e.g., MRI, CT, ultrasound, X-ray, etc.) to assess its usefulness for modality classification. In our experiment we compare our method with other visual descriptors such as CEDD, CLD, Tamura, and PHOG that extract color, texture, or shape information from images. The proposed method achieved the highest classification accuracy of 74.1% among all other individual descriptors in the test, and when combined with CSD (color structure descriptor) showed better performance (78.9%) than using the shape descriptor alone.

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Static hand gesture recognition from a video

NASA Astrophysics Data System (ADS)

Rokade, Rajeshree S.; Doye, Dharmpal

2011-10-01

A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

Imaging Metastasis Using an Integrin-Targeting Chain-Shaped Nanoparticle

PubMed Central

Peiris, Pubudu M.; Toy, Randall; Doolittle, Elizabeth; Pansky, Jenna; Abramowski, Aaron; Tam, Morgan; Vicente, Peter; Tran, Emily; Hayden, Elliott; Camann, Andrew; Mayer, Aaron; Erokwu, Bernadette O.; Berman, Zachary; Wilson, David; Baskaran, Harihara; Flask, Chris A.; Keri, Ruth A.; Karathanasis, Efstathios

2012-01-01

While the enhanced permeability and retention effect may promote the preferential accumulation of nanoparticles into well-vascularized primary tumors, it is ineffective in the case of metastases hidden within a large population of normal cells. Due to their small size, high dispersion to organs, and low vascularization, metastatic tumors are less accessible to targeted nanoparticles. To tackle these challenges, we designed a nanoparticle for vascular targeting based on an αvβ3 integrin-targeted nanochain particle composed of four iron oxide nanospheres chemically linked in a linear assembly. The chain-shaped nanoparticles enabled enhanced ‘sensing’ of the tumor-associated remodeling of the vascular bed offering increased likelihood of specific recognition of metastatic tumors. Compared to spherical nanoparticles, the chain-shaped nanoparticles resulted in superior targeting of αvβ3 integrin due to geometrically enhanced multivalent docking. We performed multimodal in vivo imaging (Fluorescence Molecular Tomography and Magnetic Resonance Imaging) in a non-invasive and quantitative manner, which showed that the nanoparticles targeted metastases in the liver and lungs with high specificity in a highly aggressive breast tumor model in mice. PMID:23005348

The effects of perceptual priming on 4-year-olds' haptic-to-visual cross-modal transfer.

PubMed

Kalagher, Hilary

2013-01-01

Four-year-old children often have difficulty visually recognizing objects that were previously experienced only haptically. This experiment attempts to improve their performance in these haptic-to-visual transfer tasks. Sixty-two 4-year-old children participated in priming trials in which they explored eight unfamiliar objects visually, haptically, or visually and haptically together. Subsequently, all children participated in the same haptic-to-visual cross-modal transfer task. In this task, children haptically explored the objects that were presented in the priming phase and then visually identified a match from among three test objects, each matching the object on only one dimension (shape, texture, or color). Children in all priming conditions predominantly made shape-based matches; however, the most shape-based matches were made in the Visual and Haptic condition. All kinds of priming provided the necessary memory traces upon which subsequent haptic exploration could build a strong enough representation to enable subsequent visual recognition. Haptic exploration patterns during the cross-modal transfer task are discussed and the detailed analyses provide a unique contribution to our understanding of the development of haptic exploratory procedures.

Figure-ground effects on shape memory for objects versus holes.

PubMed

Palmer, Stephen; Davis, Janet; Nelson, Rolf; Rock, Irvin

2008-01-01

The circumstances under which the shapes of figure-versus-ground regions are perceived and remembered were investigated in three experiments that replicate, extend, and clarify Rubin's [1921 Visuell wahrgenommene Figuren (Copenhagen: Gyldendals)] classic study on this topic. In experiment 1, observers reported which of two regions they perceived as figure within ambiguous, bipartite, 2-D displays. In a later shape-recognition test, the shapes of regions previously seen as figures were remembered well, but the shapes of regions previously seen as grounds were remembered no better than novel distractor regions. In experiment 2 we examined the same question about memory for the shape of figure-versus-ground regions in nested displays in which the central region could be perceived either as a closer figure surrounded by a farther ground (ie as a solid object) or as a farther ground surrounded by a closer figure (ie as an empty hole). Unlike experiment 1, the shapes of regions initially perceived as grounds (holes) were remembered as well as those of regions initially perceived as figures (solid objects), and much better than those of novel distractor regions. In experiment 3 we further demonstrated that this outcome did not depend on the figure-ground instructions employed in experiment 2, because the same result was obtained with unambiguous 3-D cardboard displays of objects versus holes with no figure ground instructions at all. The present findings support an account of hole perception in which the shape of an intrinsic hole is encoded as a shaped, immaterial (or virtual) surface where the absence of matter is coded by a functional 'missing' symbol (analogous to a minus sign in mathematics) to represent its non-material status.

Shape Descriptors for the Quantification of Microstructures

DTIC Science & Technology

2016-01-05

SUBJECT TERMS image analysis , microstructure 16.  SECURITY CLASSIFICATION OF: 17.  LIMITATION OF       ABSTRACT 18.  NUMBER        OF Standard Form...image entropy becomes nearly linearly dependent on temperature. The image analysis approach is capable of characterizing the range of strain domain...recognition and image analysis . The main hurdle to be overcome is the vanishing of these odd order moments for shapes which are symmetric about the

Molecular Recognition Directed Self-Assembly of Supramolecular Architectures

DTIC Science & Technology

1994-06-30

TMV-Like SupraxlecuiarArchiteturc _ TMV is a simple virus consisting only of a single type of protein molecule and of a strand of ribonucleic acid (RNA...experiments have demonstrated that various substituted gallic acid derivatives can be used to construct exo-receptors with a tapered shape. 1.2...with 3,4,5-tris(p - dodecyloxybenzyloxy)benzoic acid {12-ABCr) resulted in the taper shaped structural units. 12- ABG-B1SC5 and 12-ABG-15C5

Shape in Picture: Mathematical Description of Shape in Grey-Level Images

DTIC Science & Technology

1992-09-11

representation is scale-space, derived frrr- the linear isotropic diffusion equation; recently other types of equations have been considered. Multiscale...recognition of dimensions in the general case of an arbitrary denominator is similar to that just explained. 3 Linear Inequalities in the Two-Dimensional...solid region containing all pixels of the space, whose coordinates satisfy a linear inequality. A Um C scspt fr Digital Geometry 41 s a a v--’ -0 7 O

The large-scale organization of shape processing in the ventral and dorsal pathways

PubMed Central

Culham, Jody C; Plaut, David C; Behrmann, Marlene

2017-01-01

Although shape perception is considered a function of the ventral visual pathway, evidence suggests that the dorsal pathway also derives shape-based representations. In two psychophysics and neuroimaging experiments, we characterized the response properties, topographical organization and perceptual relevance of these representations. In both pathways, shape sensitivity increased from early visual cortex to extrastriate cortex but then decreased in anterior regions. Moreover, the lateral aspect of the ventral pathway and posterior regions of the dorsal pathway were sensitive to the availability of fundamental shape properties, even for unrecognizable images. This apparent representational similarity between the posterior-dorsal and lateral-ventral regions was corroborated by a multivariate analysis. Finally, as with ventral pathway, the activation profile of posterior dorsal regions was correlated with recognition performance, suggesting a possible contribution to perception. These findings challenge a strict functional dichotomy between the pathways and suggest a more distributed model of shape processing. PMID:28980938

Dendritic cell recognition using template matching based on one-dimensional (1D) Fourier descriptors (FD)

NASA Astrophysics Data System (ADS)

Muhd Suberi, Anis Azwani; Wan Zakaria, Wan Nurshazwani; Tomari, Razali; Lau, Mei Xia

2016-07-01

Identification of Dendritic Cell (DC) particularly in the cancer microenvironment is a unique disclosure since fighting tumor from the harnessing immune system has been a novel treatment under investigation. Nowadays, the staining procedure in sorting DC can affect their viability. In this paper, a computer aided system is proposed for automatic classification of DC in peripheral blood mononuclear cell (PBMC) images. Initially, the images undergo a few steps in preprocessing to remove uneven illumination and artifacts around the cells. In segmentation, morphological operators and Canny edge are implemented to isolate the cell shapes and extract the contours. Following that, information from the contours are extracted based on Fourier descriptors, derived from one dimensional (1D) shape signatures. Eventually, cells are classified as DC by comparing template matching (TM) of established template and target images. The results show that the proposed scheme is reliable and effective to recognize DC.

Non-monotonic relationships between emotional arousal and memory for color and location.

PubMed

Boywitt, C Dennis

2015-01-01

Recent research points to the decreased diagnostic value of subjective retrieval experience for memory accuracy for emotional stimuli. While for neutral stimuli rich recollective experiences are associated with better context memory than merely familiar memories this association appears questionable for emotional stimuli. The present research tested the implicit assumption that the effect of emotional arousal on memory is monotonic, that is, steadily increasing (or decreasing) with increasing arousal. In two experiments emotional arousal was manipulated in three steps using emotional pictures and subjective retrieval experience as well as context memory were assessed. The results show an inverted U-shape relationship between arousal and recognition memory but for context memory and retrieval experience the relationship was more complex. For frame colour, context memory decreased linearly while for spatial location it followed the inverted U-shape function. The complex, non-monotonic relationships between arousal and memory are discussed as possible explanations for earlier divergent findings.

Syntactic methods of shape feature description and its application in analysis of medical images

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Tadeusiewicz, Ryszard

2000-02-01

The paper presents specialist algorithms of morphologic analysis of shapes of selected organs of abdominal cavity proposed in order to diagnose disease symptoms occurring in the main pancreatic ducts and upper segments of ureters. Analysis of the correct morphology of these structures has been conducted with the use of syntactic methods of pattern recognition. Its main objective is computer-aided support to early diagnosis of neoplastic lesions and pancreatitis based on images taken in the course of examination with the endoscopic retrograde cholangiopancreatography (ERCP) method and a diagnosis of morphological lesions in ureter based on kidney radiogram analysis. In the analysis of ERCP images, the main objective is to recognize morphological lesions in pancreas ducts characteristic for carcinoma and chronic pancreatitis. In the case of kidney radiogram analysis the aim is to diagnose local irregularity of ureter lumen. Diagnosing the above mentioned lesion has been conducted with the use of syntactic methods of pattern recognition, in particular the languages of shape features description and context-free attributed grammars. These methods allow to recognize and describe in a very efficient way the aforementioned lesions on images obtained as a result of initial image processing into diagrams of widths of the examined structures.

Impaired processing of self-face recognition in anorexia nervosa.

PubMed

Hirot, France; Lesage, Marine; Pedron, Lya; Meyer, Isabelle; Thomas, Pierre; Cottencin, Olivier; Guardia, Dewi

2016-03-01

Body image disturbances and massive weight loss are major clinical symptoms of anorexia nervosa (AN). The aim of the present study was to examine the influence of body changes and eating attitudes on self-face recognition ability in AN. Twenty-seven subjects suffering from AN and 27 control participants performed a self-face recognition task (SFRT). During the task, digital morphs between their own face and a gender-matched unfamiliar face were presented in a random sequence. Participants' self-face recognition failures, cognitive flexibility, body concern and eating habits were assessed with the Self-Face Recognition Questionnaire (SFRQ), Trail Making Test (TMT), Body Shape Questionnaire (BSQ) and Eating Disorder Inventory-2 (EDI-2), respectively. Subjects suffering from AN exhibited significantly greater difficulties than control participants in identifying their own face (p = 0.028). No significant difference was observed between the two groups for TMT (all p > 0.1, non-significant). Regarding predictors of self-face recognition skills, there was a negative correlation between SFRT and body mass index (p = 0.01) and a positive correlation between SFRQ and EDI-2 (p < 0.001) or BSQ (p < 0.001). Among factors involved, nutritional status and intensity of eating disorders could play a part in impaired self-face recognition.

Exploring the feasibility of traditional image querying tasks for industrial radiographs

NASA Astrophysics Data System (ADS)

Bray, Iliana E.; Tsai, Stephany J.; Jimenez, Edward S.

2015-08-01

Although there have been great strides in object recognition with optical images (photographs), there has been comparatively little research into object recognition for X-ray radiographs. Our exploratory work contributes to this area by creating an object recognition system designed to recognize components from a related database of radiographs. Object recognition for radiographs must be approached differently than for optical images, because radiographs have much less color-based information to distinguish objects, and they exhibit transmission overlap that alters perceived object shapes. The dataset used in this work contained more than 55,000 intermixed radiographs and photographs, all in a compressed JPEG form and with multiple ways of describing pixel information. For this work, a robust and efficient system is needed to combat problems presented by properties of the X-ray imaging modality, the large size of the given database, and the quality of the images contained in said database. We have explored various pre-processing techniques to clean the cluttered and low-quality images in the database, and we have developed our object recognition system by combining multiple object detection and feature extraction methods. We present the preliminary results of the still-evolving hybrid object recognition system.

Microscopic prediction of speech recognition for listeners with normal hearing in noise using an auditory model.

PubMed

Jürgens, Tim; Brand, Thomas

2009-11-01

This study compares the phoneme recognition performance in speech-shaped noise of a microscopic model for speech recognition with the performance of normal-hearing listeners. "Microscopic" is defined in terms of this model twofold. First, the speech recognition rate is predicted on a phoneme-by-phoneme basis. Second, microscopic modeling means that the signal waveforms to be recognized are processed by mimicking elementary parts of human's auditory processing. The model is based on an approach by Holube and Kollmeier [J. Acoust. Soc. Am. 100, 1703-1716 (1996)] and consists of a psychoacoustically and physiologically motivated preprocessing and a simple dynamic-time-warp speech recognizer. The model is evaluated while presenting nonsense speech in a closed-set paradigm. Averaged phoneme recognition rates, specific phoneme recognition rates, and phoneme confusions are analyzed. The influence of different perceptual distance measures and of the model's a-priori knowledge is investigated. The results show that human performance can be predicted by this model using an optimal detector, i.e., identical speech waveforms for both training of the recognizer and testing. The best model performance is yielded by distance measures which focus mainly on small perceptual distances and neglect outliers.

Microscopic prediction of speech intelligibility in spatially distributed speech-shaped noise for normal-hearing listeners.

PubMed

Geravanchizadeh, Masoud; Fallah, Ali

2015-12-01

A binaural and psychoacoustically motivated intelligibility model, based on a well-known monaural microscopic model is proposed. This model simulates a phoneme recognition task in the presence of spatially distributed speech-shaped noise in anechoic scenarios. In the proposed model, binaural advantage effects are considered by generating a feature vector for a dynamic-time-warping speech recognizer. This vector consists of three subvectors incorporating two monaural subvectors to model the better-ear hearing, and a binaural subvector to simulate the binaural unmasking effect. The binaural unit of the model is based on equalization-cancellation theory. This model operates blindly, which means separate recordings of speech and noise are not required for the predictions. Speech intelligibility tests were conducted with 12 normal hearing listeners by collecting speech reception thresholds (SRTs) in the presence of single and multiple sources of speech-shaped noise. The comparison of the model predictions with the measured binaural SRTs, and with the predictions of a macroscopic binaural model called extended equalization-cancellation, shows that this approach predicts the intelligibility in anechoic scenarios with good precision. The square of the correlation coefficient (r(2)) and the mean-absolute error between the model predictions and the measurements are 0.98 and 0.62 dB, respectively.

Molecularly imprinted polymer for glutathione by modified precipitation polymerization and its application to determination of glutathione in supplements.

PubMed

Nakamura, Yukari; Masumoto, Shizuka; Matsunaga, Hisami; Haginaka, Jun

2017-09-10

Molecularly imprinted polymers (MIP) particles for glutathione (GSH) with a narrow particle size distribution were prepared by modified precipitation polymerization using methacrylic acid as a functional monomer, divinylbenzene as a crosslinker and water as a co-solvent. The particle diameters of the MIP and non-imprinted polymer (NIP) prepared under the optimum conditions were 3.81±0.95 (average±standard deviation) and 3.39±1.22μm, respectively. The retention and molecular-recognition properties of the prepared MIP were evaluated using a mixture of acetonitrile and water as a mobile phase in hydrophilic interaction chromatography. With an increase of acetonitrile content, the retention factor of GSH was increased on the MIP. In addition to shape recognition, hydrophilic interactions seem to work for the recognition of GSH on the MIP. The MIP had a specific molecular-recognition ability for GSH, while glutathione disulfide, l-Glu, l-Cys, Gly-Gly and l-Cys-Gly could not be retained or recognized on the MIP. The effect of column temperature revealed that the separation of GSH on the MIP was entropically driven. Binding experiments and Scatchard analyses revealed that one binding sites were formed on both the MIP and NIP, while the MIP gave higher affinity and capacity for GSH than the NIP. Furthermore, the MIP was successfully applied for determination of GSH in the supplements. Copyright © 2016 Elsevier B.V. All rights reserved.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

Increased anxiety-like behavior but no cognitive impairments in adult rats exposed to constant light conditions during perinatal development.

PubMed

Roman, Erika; Karlsson, Oskar

2013-11-01

Shift-work is suggested to affect fetal development negatively. In particular, maternal hormonal disturbance arising from sleep deprivation or circadian rhythm changes may disturb fetal growth or lead to complications during pregnancy. Exposure to constant light is an environmental stressor that can affect the circadian system and has been shown to induce neurochemical and behavioral changes when used during the prenatal and/or postnatal period in experimental animals. However, studies investigating long-term effects of constant light in the offspring are sparse. An accidental power outage resulted in pregnant females being housed under constant light (LL) conditions for seven days of the offspring perinatal development (embryonic day 20 to postnatal day 4). The long-term effects of constant light on the behavior in the adult offspring were assessed by means of open field, object recognition, and water maze tests. In adulthood, LL-animals displayed an intact recognition memory and no deficits in spatial learning or memory. In the open field test, LL-animals exhibited higher anxiety-like behavior, observed as significantly more thigmotaxis and less ambulation. These results were confirmed in the other behavioral tests as the LL-animals spent less time exploring the objects in the object recognition test, and showed thigmotactic behavior also in the water maze test. The results confirm that early life experience can cause changes in brain development that shape brain function and add to the sparse literature on long-term effects of constant light conditions during perinatal development on specific behaviors in adulthood.

Does input influence uptake? Links between maternal talk, processing speed and vocabulary size in Spanish-learning children

PubMed Central

Hurtado, Nereyda; Marchman, Virginia A.; Fernald, Anne

2010-01-01

It is well established that variation in caregivers' speech is associated with language outcomes, yet little is known about the learning principles that mediate these effects. This longitudinal study (n = 27) explores whether Spanish-learning children's early experiences with language predict efficiency in real-time comprehension and vocabulary learning. Measures of mothers' speech at 18 months were examined in relation to children's speech processing efficiency and reported vocabulary at 18 and 24 months. Children of mothers who provided more input at 18 months knew more words and were faster in word recognition at 24 months. Moreover, multiple regression analyses indicated that the influences of caregiver speech on speed of word recognition and vocabulary were largely overlapping. This study provides the first evidence that input shapes children's lexical processing efficiency and that vocabulary growth and increasing facility in spoken word comprehension work together to support the uptake of the information that rich input affords the young language learner. PMID:19046145

Synthetic tripodal receptors for carbohydrates. Pyrrole, a hydrogen bonding partner for saccharidic hydroxyls.

PubMed

Francesconi, Oscar; Gentili, Matteo; Roelens, Stefano

2012-09-07

The carbohydrate recognition properties of synthetic tripodal receptors relying on H-bonding interactions have highlighted the crucial role played by the functional groups matching saccharidic hydroxyls. Herein, pyrrole and pyridine, which emerged as two of the most effective H-bonding groups, were quantitatively compared through their isostructural substitution within the architecture of a shape-persistent bicyclic cage receptor. NMR and ITC binding studies gave for the pyrrolic receptor a 20-fold larger affinity toward octyl-β-d-glucopyranoside in CDCl(3), demonstrating the superior recognition properties of pyrrole under conditions in which differences would depend on the intrinsic binding ability of the two groups. The three-dimensional structures of the two glucoside complexes in solution were elucidated by combined NMR and molecular mechanics computational techniques, showing that the origin of the stability difference between the two closely similar complex structures resides in the ability of pyrrole to establish shorter/stronger H-bonds with the glucosidic ligand compared to pyridine.

A novel binary shape context for 3D local surface description

NASA Astrophysics Data System (ADS)

Dong, Zhen; Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Li, Bijun; Zang, Yufu

2017-08-01

3D local surface description is now at the core of many computer vision technologies, such as 3D object recognition, intelligent driving, and 3D model reconstruction. However, most of the existing 3D feature descriptors still suffer from low descriptiveness, weak robustness, and inefficiency in both time and memory. To overcome these challenges, this paper presents a robust and descriptive 3D Binary Shape Context (BSC) descriptor with high efficiency in both time and memory. First, a novel BSC descriptor is generated for 3D local surface description, and the performance of the BSC descriptor under different settings of its parameters is analyzed. Next, the descriptiveness, robustness, and efficiency in both time and memory of the BSC descriptor are evaluated and compared to those of several state-of-the-art 3D feature descriptors. Finally, the performance of the BSC descriptor for 3D object recognition is also evaluated on a number of popular benchmark datasets, and an urban-scene dataset is collected by a terrestrial laser scanner system. Comprehensive experiments demonstrate that the proposed BSC descriptor obtained high descriptiveness, strong robustness, and high efficiency in both time and memory and achieved high recognition rates of 94.8%, 94.1% and 82.1% on the considered UWA, Queen, and WHU datasets, respectively.

A self-teaching image processing and voice-recognition-based, intelligent and interactive system to educate visually impaired children

NASA Astrophysics Data System (ADS)

Iqbal, Asim; Farooq, Umar; Mahmood, Hassan; Asad, Muhammad Usman; Khan, Akrama; Atiq, Hafiz Muhammad

2010-02-01

A self teaching image processing and voice recognition based system is developed to educate visually impaired children, chiefly in their primary education. System comprises of a computer, a vision camera, an ear speaker and a microphone. Camera, attached with the computer system is mounted on the ceiling opposite (on the required angle) to the desk on which the book is placed. Sample images and voices in the form of instructions and commands of English, Urdu alphabets, Numeric Digits, Operators and Shapes are already stored in the database. A blind child first reads the embossed character (object) with the help of fingers than he speaks the answer, name of the character, shape etc into the microphone. With the voice command of a blind child received by the microphone, image is taken by the camera which is processed by MATLAB® program developed with the help of Image Acquisition and Image processing toolbox and generates a response or required set of instructions to child via ear speaker, resulting in self education of a visually impaired child. Speech recognition program is also developed in MATLAB® with the help of Data Acquisition and Signal Processing toolbox which records and process the command of the blind child.

Ciproxifan, an H3 receptor antagonist, improves short-term recognition memory impaired by isoflurane anesthesia.

PubMed

Ding, Fang; Zheng, Limin; Liu, Min; Chen, Rongfa; Leung, L Stan; Luo, Tao

2016-08-01

Exposure to volatile anesthetics has been reported to cause temporary or sustained impairments in learning and memory in pre-clinical studies. The selective antagonists of the histamine H3 receptors (H3R) are considered to be a promising group of novel therapeutic agents for the treatment of cognitive disorders. The aim of this study was to evaluate the effect of H3R antagonist ciproxifan on isoflurane-induced deficits in an object recognition task. Adult C57BL/6 J mice were exposed to isoflurane (1.3 %) or vehicle gas for 2 h. The object recognition tests were carried at 24 h or 7 days after exposure to anesthesia to exploit the tendency of mice to prefer exploring novel objects in an environment when a familiar object is also present. During the training phase, two identical objects were placed in two defined sites of the chamber. During the test phase, performed 1 or 24 h after the training phase, one of the objects was replaced by a new object with a different shape. The time spent exploring each object was recorded. A robust deficit in object recognition memory occurred 1 day after exposure to isoflurane anesthesia. Isoflurane-treated mice spent significantly less time exploring a novel object at 1 h but not at 24 h after the training phase. The deficit in short-term memory was reversed by the administration of ciproxifan 30 min before behavioral training. Isoflurane exposure induces reversible deficits in object recognition memory. Ciproxifan appears to be a potential therapeutic agent for improving post-anesthesia cognitive memory performance.

The role of temporal call structure in species recognition of male Allobates talamancae (Cope, 1875): (Anura: Dendrobatidae).

PubMed

Kollarits, Dennis; Wappl, Christian; Ringler, Max

2017-01-30

Acoustic species recognition in anurans depends on spectral and temporal characteristics of the advertisement call. The recognition space of a species is shaped by the likelihood of heterospecific acoustic interference. The dendrobatid frogs Allobates talamancae (Cope, 1875) and Silverstoneia flotator (Dunn, 1931) occur syntopically in south-west Costa Rica. A previous study showed that these two species avoid acoustic interference by spectral stratification. In this study, the role of the temporal call structure in the advertisement call of A. talamancae was analyzed, in particular the internote-interval duration in providing species specific temporal cues. In playback trials, artificial advertisement calls with internote-intervals deviating up to ± 90 % from the population mean internote-interval were broadcast to vocally active territorial males. The phonotactic reactions of the males indicated that, unlike in closely related species, internote-interval duration is not a call property essential for species recognition in A. talamancae . However, temporal call structure may be used for species recognition when the likelihood of heterospecific interference is high. Also, the close-encounter courtship call of male A. talamancae is described.

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Cross-modal working memory binding and word recognition skills: how specific is the link?

PubMed

Wang, Shinmin; Allen, Richard J

2018-04-01

Recent research has suggested that the creation of temporary bound representations of information from different sources within working memory uniquely relates to word recognition abilities in school-age children. However, it is unclear to what extent this link is attributable specifically to the binding ability for cross-modal information. This study examined the performance of Grade 3 (8-9 years old) children on binding tasks requiring either temporary association formation of two visual items (i.e., within-modal binding) or pairs of visually presented abstract shapes and auditorily presented nonwords (i.e., cross-modal binding). Children's word recognition skills were related to performance on the cross-modal binding task but not on the within-modal binding task. Further regression models showed that cross-modal binding memory was a significant predictor of word recognition when memory for its constituent elements, general abilities, and crucially, within-modal binding memory were taken into account. These findings may suggest a specific link between the ability to bind information across modalities within working memory and word recognition skills.

Spatial-frequency cutoff requirements for pattern recognition in central and peripheral vision

PubMed Central

Kwon, MiYoung; Legge, Gordon E.

2011-01-01

It is well known that object recognition requires spatial frequencies exceeding some critical cutoff value. People with central scotomas who rely on peripheral vision have substantial difficulty with reading and face recognition. Deficiencies of pattern recognition in peripheral vision, might result in higher cutoff requirements, and may contribute to the functional problems of people with central-field loss. Here we asked about differences in spatial-cutoff requirements in central and peripheral vision for letter and face recognition. The stimuli were the 26 letters of the English alphabet and 26 celebrity faces. Each image was blurred using a low-pass filter in the spatial frequency domain. Critical cutoffs (defined as the minimum low-pass filter cutoff yielding 80% accuracy) were obtained by measuring recognition accuracy as a function of cutoff (in cycles per object). Our data showed that critical cutoffs increased from central to peripheral vision by 20% for letter recognition and by 50% for face recognition. We asked whether these differences could be accounted for by central/peripheral differences in the contrast sensitivity function (CSF). We addressed this question by implementing an ideal-observer model which incorporates empirical CSF measurements and tested the model on letter and face recognition. The success of the model indicates that central/peripheral differences in the cutoff requirements for letter and face recognition can be accounted for by the information content of the stimulus limited by the shape of the human CSF, combined with a source of internal noise and followed by an optimal decision rule. PMID:21854800

A fuzzy clustering algorithm to detect planar and quadric shapes

NASA Technical Reports Server (NTRS)

Krishnapuram, Raghu; Frigui, Hichem; Nasraoui, Olfa

1992-01-01

In this paper, we introduce a new fuzzy clustering algorithm to detect an unknown number of planar and quadric shapes in noisy data. The proposed algorithm is computationally and implementationally simple, and it overcomes many of the drawbacks of the existing algorithms that have been proposed for similar tasks. Since the clustering is performed in the original image space, and since no features need to be computed, this approach is particularly suited for sparse data. The algorithm may also be used in pattern recognition applications.

Conceptus-derived prostaglandins regulate gene expression in the endometrium prior to pregnancy recognition in ruminants

PubMed Central

Spencer, Thomas E.; Forde, Niamh; Dorniak, Piotr; Hansen, Thomas R.; Romero, Jared J.; Lonergan, Patrick

2013-01-01

In cattle, the blastocyst hatches from the zona pellucida on days 8 to 9 and then forms a conceptus that grows and elongates into an ovoid and then filamentous shape between days 9 and 16. The growing conceptus synthesizes and secretes prostaglandins and interferon tau. Our hypothesis was that the ovoid conceptus exerts a local effect on the endometrium prior to maternal recognition of pregnancy on day 16 in cattle. In Study One, synchronized cyclic heifers received nothing or 20 in vitro produced blastocysts on day 7, and uteri were collected on day 13. Interferon tau was not detected by radioimmunoassay in the uterine flush of pregnant heifers containing multiple ovoid conceptuses; however, total prostaglandin levels were higher in the uterine lumen of pregnant as compared to cyclic heifers. Microarray analysis revealed that 44 genes were increased in the endometrium of day 13 pregnant as compared to cyclic heifers, and many of those genes were classical Type I IFN-stimulated genes (ISGs). Studies Two and Three determined effects of infusing prostaglandins at the levels produced by the elongating day 14 conceptus into the uterine lumen of cyclic ewes on ISG expression in the endometrium. Results indicated that prostaglandin infusion increased the abundance of several ISGs in the endometrium. These studies support the hypothesis that the day 13 conceptus secretes prostaglandins that act locally in a paracrine manner to alter gene expression in the endometrium prior to pregnancy recognition in cattle. PMID:23966582

Implicit multisensory associations influence voice recognition.

PubMed

von Kriegstein, Katharina; Giraud, Anne-Lise

2006-10-01

Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.

Sentence intelligibility during segmental interruption and masking by speech-modulated noise: Effects of age and hearing loss

PubMed Central

Fogerty, Daniel; Ahlstrom, Jayne B.; Bologna, William J.; Dubno, Judy R.

2015-01-01

This study investigated how single-talker modulated noise impacts consonant and vowel cues to sentence intelligibility. Younger normal-hearing, older normal-hearing, and older hearing-impaired listeners completed speech recognition tests. All listeners received spectrally shaped speech matched to their individual audiometric thresholds to ensure sufficient audibility with the exception of a second younger listener group who received spectral shaping that matched the mean audiogram of the hearing-impaired listeners. Results demonstrated minimal declines in intelligibility for older listeners with normal hearing and more evident declines for older hearing-impaired listeners, possibly related to impaired temporal processing. A correlational analysis suggests a common underlying ability to process information during vowels that is predictive of speech-in-modulated noise abilities. Whereas, the ability to use consonant cues appears specific to the particular characteristics of the noise and interruption. Performance declines for older listeners were mostly confined to consonant conditions. Spectral shaping accounted for the primary contributions of audibility. However, comparison with the young spectral controls who received identical spectral shaping suggests that this procedure may reduce wideband temporal modulation cues due to frequency-specific amplification that affected high-frequency consonants more than low-frequency vowels. These spectral changes may impact speech intelligibility in certain modulation masking conditions. PMID:26093436

Name that tune: Melodic recognition by songbirds.

PubMed

Templeton, Christopher N

2016-12-01

Recent findings have indicated that European starlings perceive overall spectral shape and use this, rather than absolute pitch or timbre, to generalize between similar melodic progressions. This finding highlights yet another parallel between human and avian vocal communication systems and has many biological implications.

Ocular biometrics by score-level fusion of disparate experts.

PubMed

Proença, Hugo

2014-12-01

The concept of periocular biometrics emerged to improve the robustness of iris recognition to degraded data. Being a relatively recent topic, most of the periocular recognition algorithms work in a holistic way and apply a feature encoding/matching strategy without considering each biological component in the periocular area. This not only augments the correlation between the components in the resulting biometric signature, but also increases the sensitivity to particular data covariates. The main novelty in this paper is to propose a periocular recognition ensemble made of two disparate components: 1) one expert analyses the iris texture and exhaustively exploits the multispectral information in visible-light data and 2) another expert parameterizes the shape of eyelids and defines a surrounding dimensionless region-of-interest, from where statistics of the eyelids, eyelashes, and skin wrinkles/furrows are encoded. Both experts work on disjoint regions of the periocular area and meet three important properties. First, they produce practically independent responses, which is behind the better performance of the ensemble when compared to the best individual recognizer. Second, they do not share particularly sensitivity to any image covariate, which accounts for augmenting the robustness against degraded data. Finally, it should be stressed that we disregard information in the periocular region that can be easily forged (e.g., shape of eyebrows), which constitutes an active anticounterfeit measure. An empirical evaluation was conducted on two public data sets (FRGC and UBIRIS.v2), and points for consistent improvements in performance of the proposed ensemble over the state-of-the-art periocular recognition algorithms.

Practical automatic Arabic license plate recognition system

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Agaian, Sos; Saleh, Hani

2011-02-01

Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

Generation of oculomotor images during tasks requiring visual recognition of polygons.

PubMed

Olivier, G; de Mendoza, J L

2001-06-01

This paper concerns the contribution of mentally simulated ocular exploration to generation of a visual mental image. In Exp. 1, repeated exploration of the outlines of an irregular decagon allowed an incidental learning of the shape. Analyses showed subjects memorized their ocular movements rather than the polygon. In Exp. 2, exploration of a reversible figure such as a Necker cube varied in opposite directions. Then, both perspective possibilities are presented. The perspective the subjects recognized depended on the way they explored the ambiguous figure. In both experiments, during recognition the subjects recalled a visual mental image of the polygon they compared with the different polygons proposed for recognition. To interpret the data, hypotheses concerning common processes underlying both motor intention of ocular movements and generation of a visual image are suggested.

Products recognition on shop-racks from local scale-invariant features

NASA Astrophysics Data System (ADS)

Zawistowski, Jacek; Kurzejamski, Grzegorz; Garbat, Piotr; Naruniec, Jacek

2016-04-01

This paper presents a system designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. System uses well known binary keypoint detection algorithms for finding characteristic points in the image. One of the main idea is object recognition based on Implicit Shape Model method. Authors of the article proposed many improvements of the algorithm. Originally fiducial points are matched with a very simple function. This leads to the limitations in the number of objects parts being success- fully separated, while various methods of classification may be validated in order to achieve higher performance. Such an extension implies research on training procedure able to deal with many objects categories. Proposed solution opens a new possibilities for many algorithms demanding fast and robust multi-object recognition.

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

PubMed Central

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease. PMID:27977767

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

PubMed

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease.

Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar

NASA Astrophysics Data System (ADS)

Maas, Christian; Schmalzl, Jörg

2013-08-01

Ground Penetrating Radar (GPR) is used for the localization of supply lines, land mines, pipes and many other buried objects. These objects can be recognized in the recorded data as reflection hyperbolas with a typical shape depending on depth and material of the object and the surrounding material. To obtain the parameters, the shape of the hyperbola has to be fitted. In the last years several methods were developed to automate this task during post-processing. In this paper we show another approach for the automated localization of reflection hyperbolas in GPR data by solving a pattern recognition problem in grayscale images. In contrast to other methods our detection program is also able to immediately mark potential objects in real-time. For this task we use a version of the Viola-Jones learning algorithm, which is part of the open source library "OpenCV". This algorithm was initially developed for face recognition, but can be adapted to any other simple shape. In our program it is used to narrow down the location of reflection hyperbolas to certain areas in the GPR data. In order to extract the exact location and the velocity of the hyperbolas we apply a simple Hough Transform for hyperbolas. Because the Viola-Jones Algorithm reduces the input for the computational expensive Hough Transform dramatically the detection system can also be implemented on normal field computers, so on-site application is possible. The developed detection system shows promising results and detection rates in unprocessed radargrams. In order to improve the detection results and apply the program to noisy radar images more data of different GPR systems as input for the learning algorithm is necessary.

Control chart pattern recognition using RBF neural network with new training algorithm and practical features.

PubMed

Addeh, Abdoljalil; Khormali, Aminollah; Golilarz, Noorbakhsh Amiri

2018-05-04

The control chart patterns are the most commonly used statistical process control (SPC) tools to monitor process changes. When a control chart produces an out-of-control signal, this means that the process has been changed. In this study, a new method based on optimized radial basis function neural network (RBFNN) is proposed for control chart patterns (CCPs) recognition. The proposed method consists of four main modules: feature extraction, feature selection, classification and learning algorithm. In the feature extraction module, shape and statistical features are used. Recently, various shape and statistical features have been presented for the CCPs recognition. In the feature selection module, the association rules (AR) method has been employed to select the best set of the shape and statistical features. In the classifier section, RBFNN is used and finally, in RBFNN, learning algorithm has a high impact on the network performance. Therefore, a new learning algorithm based on the bees algorithm has been used in the learning module. Most studies have considered only six patterns: Normal, Cyclic, Increasing Trend, Decreasing Trend, Upward Shift and Downward Shift. Since three patterns namely Normal, Stratification, and Systematic are very similar to each other and distinguishing them is very difficult, in most studies Stratification and Systematic have not been considered. Regarding to the continuous monitoring and control over the production process and the exact type detection of the problem encountered during the production process, eight patterns have been investigated in this study. The proposed method is tested on a dataset containing 1600 samples (200 samples from each pattern) and the results showed that the proposed method has a very good performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Parameterization of Shape and Compactness in Object-based Image Classification Using Quickbird-2 Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2016-12-01

In recent years, object based image analysis (OBIA) has spread out and become a widely accepted technique for the analysis of remotely sensed data. OBIA deals with grouping pixels into homogenous objects based on spectral, spatial and textural features of contiguous pixels in an image. The first stage of OBIA, named as image segmentation, is the most prominent part of object recognition. In this study, multiresolution segmentation, which is a region-based approach, was employed to construct image objects. In the application of multi-resolution, three parameters, namely shape, compactness and scale must be set by the analyst. Segmentation quality remarkably influences the fidelity of the thematic maps and accordingly the classification accuracy. Therefore, it is of great importance to search and set optimal values for the segmentation parameters. In the literature, main focus has been on the definition of scale parameter, assuming that the effect of shape and compactness parameters is limited in terms of achieved classification accuracy. The aim of this study is to deeply analyze the influence of shape/compactness parameters by varying their values while using the optimal scale parameter determined by the use of Estimation of Scale Parameter (ESP-2) approach. A pansharpened Qickbird-2 image covering Trabzon, Turkey was employed to investigate the objectives of the study. For this purpose, six different combinations of shape/compactness were utilized to make deductions on the behavior of shape and compactness parameters and optimal setting for all parameters as a whole. Objects were assigned to classes using nearest neighbor classifier in all segmentation observations and equal number of pixels was randomly selected to calculate accuracy metrics. The highest overall accuracy (92.3%) was achieved by setting the shape/compactness criteria to 0.3/0.3. The results of this study indicate that shape/compactness parameters can have significant effect on classification accuracy with 4% change in overall accuracy. Also, statistical significance of differences in accuracy was tested using the McNemar's test and found that the difference between poor and optimal setting of shape/compactness parameters was statistically significant, suggesting a search for optimal parameterization instead of default setting.

The role of shape recognition in figure/ground perception in infancy.

PubMed

White, Hannah; Jubran, Rachel; Heck, Alison; Chroust, Alyson; Bhatt, Ramesh S

2018-04-30

In this study we sought to determine whether infants, like adults, utilize previous experience to guide figure/ground processing. After familiarization to a shape, 5-month-olds preferentially attended to the side of an ambiguous figure/ground test stimulus corresponding to that shape, suggesting that they were viewing that portion as the figure. Infants' failure to exhibit this preference in a control condition in which both sides of the test stimulus were displayed as figures indicated that the results in the experimental condition were not due to a preference between two figure shapes. These findings demonstrate for the first time that figure/ground processing in infancy is sensitive to top-down influence. Thus, a critical aspect of figure/ground processing is functional early in life.

Symbolic feature detection for image understanding

NASA Astrophysics Data System (ADS)

Aslan, Sinem; Akgül, Ceyhun Burak; Sankur, Bülent

2014-03-01

In this study we propose a model-driven codebook generation method used to assign probability scores to pixels in order to represent underlying local shapes they reside in. In the first version of the symbol library we limited ourselves to photometric and similarity transformations applied on eight prototypical shapes of flat plateau , ramp, valley, ridge, circular and elliptic respectively pit and hill and used randomized decision forest as the statistical classifier to compute shape class ambiguity of each pixel. We achieved90% accuracy in identification of known objects from alternate views, however, we could not outperform texture, global and local shape methods, but only color-based method in recognition of unknown objects. We present a progress plan to be accomplished as a future work to improve the proposed approach further.

Road traffic sign detection and classification from mobile LiDAR point clouds

NASA Astrophysics Data System (ADS)

Weng, Shengxia; Li, Jonathan; Chen, Yiping; Wang, Cheng

2016-03-01

Traffic signs are important roadway assets that provide valuable information of the road for drivers to make safer and easier driving behaviors. Due to the development of mobile mapping systems that can efficiently acquire dense point clouds along the road, automated detection and recognition of road assets has been an important research issue. This paper deals with the detection and classification of traffic signs in outdoor environments using mobile light detection and ranging (Li- DAR) and inertial navigation technologies. The proposed method contains two main steps. It starts with an initial detection of traffic signs based on the intensity attributes of point clouds, as the traffic signs are always painted with highly reflective materials. Then, the classification of traffic signs is achieved based on the geometric shape and the pairwise 3D shape context. Some results and performance analyses are provided to show the effectiveness and limits of the proposed method. The experimental results demonstrate the feasibility and effectiveness of the proposed method in detecting and classifying traffic signs from mobile LiDAR point clouds.

Learning from the Messengers: Innate Sensing of Viruses and Cytokine Regulation of Immunity—Clues for Treatments and Vaccines

PubMed Central

Melchjorsen, Jesper

2013-01-01

Virus infections are a major global public health concern, and only via substantial knowledge of virus pathogenesis and antiviral immune responses can we develop and improve medical treatments, and preventive and therapeutic vaccines. Innate immunity and the shaping of efficient early immune responses are essential for control of viral infections. In order to trigger an efficient antiviral defense, the host senses the invading microbe via pattern recognition receptors (PRRs), recognizing distinct conserved pathogen-associated molecular patterns (PAMPs). The innate sensing of the invading virus results in intracellular signal transduction and subsequent production of interferons (IFNs) and proinflammatory cytokines. Cytokines, including IFNs and chemokines, are vital molecules of antiviral defense regulating cell activation, differentiation of cells, and, not least, exerting direct antiviral effects. Cytokines shape and modulate the immune response and IFNs are principle antiviral mediators initiating antiviral response through induction of antiviral proteins. In the present review, I describe and discuss the current knowledge on early virus–host interactions, focusing on early recognition of virus infection and the resulting expression of type I and type III IFNs, proinflammatory cytokines, and intracellular antiviral mediators. In addition, the review elucidates how targeted stimulation of innate sensors, such as toll-like receptors (TLRs) and intracellular RNA and DNA sensors, may be used therapeutically. Moreover, I present and discuss data showing how current antimicrobial therapies, including antibiotics and antiviral medication, may interfere with, or improve, immune response. PMID:23435233

Molecular Imprinting Applications in Forensic Science

PubMed Central

Yılmaz, Erkut; Garipcan, Bora; Patra, Hirak K.; Uzun, Lokman

2017-01-01

Producing molecular imprinting-based materials has received increasing attention due to recognition selectivity, stability, cast effectiveness, and ease of production in various forms for a wide range of applications. The molecular imprinting technique has a variety of applications in the areas of the food industry, environmental monitoring, and medicine for diverse purposes like sample pretreatment, sensing, and separation/purification. A versatile usage, stability and recognition capabilities also make them perfect candidates for use in forensic sciences. Forensic science is a demanding area and there is a growing interest in molecularly imprinted polymers (MIPs) in this field. In this review, recent molecular imprinting applications in the related areas of forensic sciences are discussed while considering the literature of last two decades. Not only direct forensic applications but also studies of possible forensic value were taken into account like illicit drugs, banned sport drugs, effective toxins and chemical warfare agents in a review of over 100 articles. The literature was classified according to targets, material shapes, production strategies, detection method, and instrumentation. We aimed to summarize the current applications of MIPs in forensic science and put forth a projection of their potential uses as promising alternatives for benchmark competitors. PMID:28350333

What can we learn from learning models about sensitivity to letter-order in visual word recognition?

PubMed Central

Lerner, Itamar; Armstrong, Blair C.; Frost, Ram

2014-01-01

Recent research on the effects of letter transposition in Indo-European Languages has shown that readers are surprisingly tolerant of these manipulations in a range of tasks. This evidence has motivated the development of new computational models of reading that regard flexibility in positional coding to be a core and universal principle of the reading process. Here we argue that such approach does not capture cross-linguistic differences in transposed-letter effects, nor do they explain them. To address this issue, we investigated how a simple domain-general connectionist architecture performs in tasks such as letter-transposition and letter substitution when it had learned to process words in the context of different linguistic environments. The results show that in spite of of the neurobiological noise involved in registering letter-position in all languages, flexibility and inflexibility in coding letter order is also shaped by the statistical orthographic properties of words in a language, such as the relative prevalence of anagrams. Our learning model also generated novel predictions for targeted empirical research, demonstrating a clear advantage of learning models for studying visual word recognition. PMID:25431521

Molecular Imprinting Applications in Forensic Science.

PubMed

Yılmaz, Erkut; Garipcan, Bora; Patra, Hirak K; Uzun, Lokman

2017-03-28

Producing molecular imprinting-based materials has received increasing attention due to recognition selectivity, stability, cast effectiveness, and ease of production in various forms for a wide range of applications. The molecular imprinting technique has a variety of applications in the areas of the food industry, environmental monitoring, and medicine for diverse purposes like sample pretreatment, sensing, and separation/purification. A versatile usage, stability and recognition capabilities also make them perfect candidates for use in forensic sciences. Forensic science is a demanding area and there is a growing interest in molecularly imprinted polymers (MIPs) in this field. In this review, recent molecular imprinting applications in the related areas of forensic sciences are discussed while considering the literature of last two decades. Not only direct forensic applications but also studies of possible forensic value were taken into account like illicit drugs, banned sport drugs, effective toxins and chemical warfare agents in a review of over 100 articles. The literature was classified according to targets, material shapes, production strategies, detection method, and instrumentation. We aimed to summarize the current applications of MIPs in forensic science and put forth a projection of their potential uses as promising alternatives for benchmark competitors.

Is a Pink Cow Still a Cow? Individual Differences in Toddlers' Vocabulary Knowledge and Lexical Representations.

PubMed

Perry, Lynn K; Saffran, Jenny R

2017-05-01

When a toddler knows a word, what does she actually know? Many categories have multiple relevant properties; for example, shape and color are relevant to membership in the category banana. How do toddlers prioritize these properties when recognizing familiar words, and are there systematic differences among children? In this study, toddlers viewed pairs of objects associated with prototypical colors. On some trials, objects were typically colored (e.g., Holstein cow and pink pig); on other trials, colors were switched (e.g., pink cow and Holstein-patterned pig). On each trial, toddlers were directed to find a target object. Overall, recognition was disrupted when colors were switched, as measured by eye movements. Moreover, individual differences in vocabularies predicted recognition differences: Toddlers who say fewer shape-based words were more disrupted by color switches. "Knowing" a word may not mean the same thing for all toddlers; different toddlers prioritize different facets of familiar objects in their lexical representations. Copyright © 2016 Cognitive Science Society, Inc.

Segregation and persistence of form in the lateral occipital complex.

PubMed

Ferber, Susanne; Humphrey, G Keith; Vilis, Tutis

2005-01-01

While the lateral occipital complex (LOC) has been shown to be implicated in object recognition, it is unclear whether this brain area is responsive to low-level stimulus-driven features or high-level representational processes. We used scrambled shape-from-motion displays to disambiguate the presence of contours from figure-ground segregation and to measure the strength of the binding process for shapes without contours. We found persisting brain activation in the LOC for scrambled displays after the motion stopped indicating that this brain area subserves and maintains figure-ground segregation processes, a low-level function in the object processing hierarchy. In our second experiment, we found that the figure-ground segregation process has some form of spatial constancy indicating top-down influences. The persisting activation after the motion stops suggests an intermediate role in object recognition processes for this brain area and might provide further evidence for the idea that the lateral occipital complex subserves mnemonic functions mediating between iconic and short-term memory.

Identifying and detecting facial expressions of emotion in peripheral vision.

PubMed

Smith, Fraser W; Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus.

Identifying and detecting facial expressions of emotion in peripheral vision

PubMed Central

Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus. PMID:29847562

Morphological and population genomic evidence that human faces have evolved to signal individual identity.

PubMed

Sheehan, Michael J; Nachman, Michael W

2014-09-16

Facial recognition plays a key role in human interactions, and there has been great interest in understanding the evolution of human abilities for individual recognition and tracking social relationships. Individual recognition requires sufficient cognitive abilities and phenotypic diversity within a population for discrimination to be possible. Despite the importance of facial recognition in humans, the evolution of facial identity has received little attention. Here we demonstrate that faces evolved to signal individual identity under negative frequency-dependent selection. Faces show elevated phenotypic variation and lower between-trait correlations compared with other traits. Regions surrounding face-associated single nucleotide polymorphisms show elevated diversity consistent with frequency-dependent selection. Genetic variation maintained by identity signalling tends to be shared across populations and, for some loci, predates the origin of Homo sapiens. Studies of human social evolution tend to emphasize cognitive adaptations, but we show that social evolution has shaped patterns of human phenotypic and genetic diversity as well.

Automatic anatomy recognition on CT images with pathology

NASA Astrophysics Data System (ADS)

Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

2016-03-01

Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

Logo image clustering based on advanced statistics

NASA Astrophysics Data System (ADS)

Wei, Yi; Kamel, Mohamed; He, Yiwei

2007-11-01

In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.

Optimized face recognition algorithm using radial basis function neural networks and its practical applications.

PubMed

Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold

2015-09-01

In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

An audiovisual emotion recognition system

NASA Astrophysics Data System (ADS)

Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

2007-12-01

Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

The role of color in the implicit memory performance of healthy older adults and individuals with Alzheimer's disease.

PubMed

Lloyd-Jones, Toby J

2005-01-01

Although the Alzheimer's disease (AD) patients in this study were severely impaired in recognition performance, their naming performance demonstrated normal priming across transformations in object color. This is evidence for preserved implicit shape-based memory performance in AD patients. For colored-object decision, healthy older adult control participants but not AD patients showed priming for new associations between previously encountered object shapes and colors. The author argues, on the basis of this colored object decision performance, that the deficits present in AD do not allow shape and color to be integrated to form a novel unitized representation that can be used to benefit cognitive performance. 2005 APA

On the shape of the hospital industry long run average cost curve.

PubMed Central

Finkler, S A

1979-01-01

Empirical studies of the hospital industry have produced conflicting results with respect to the shape of the industry's long run average cost (LRAC) curve. Some of the studies have found a classical U-shaped curve. Others have produced results indicating that the LRAC curve is much closer to being L-shaped. Some theoretical support exists for both sets of findings. While classical theory predicts that the LRAC curve will be U-shaped, Alchian has presented theoretical arguments explaining why such curves would be L-shaped. This paper reconciles the results of these studies. The basis for the reconciliation is recognition of the failure of individual hospitals to produce all their individual product lines at efficient volumes. Such inefficient production is feasible and perhaps common, given the incentive structure which exists under current cost reimbursement systems. The implication of this paper is that large hospitals may have a greater potential for scale economies than has previously been recognized. PMID:528221

On the shape of the hospital industry long run average cost curve.

PubMed

Finkler, S A

1979-01-01

Empirical studies of the hospital industry have produced conflicting results with respect to the shape of the industry's long run average cost (LRAC) curve. Some of the studies have found a classical U-shaped curve. Others have produced results indicating that the LRAC curve is much closer to being L-shaped. Some theoretical support exists for both sets of findings. While classical theory predicts that the LRAC curve will be U-shaped, Alchian has presented theoretical arguments explaining why such curves would be L-shaped. This paper reconciles the results of these studies. The basis for the reconciliation is recognition of the failure of individual hospitals to produce all their individual product lines at efficient volumes. Such inefficient production is feasible and perhaps common, given the incentive structure which exists under current cost reimbursement systems. The implication of this paper is that large hospitals may have a greater potential for scale economies than has previously been recognized.

Culture: what is its effect on stress in the military?

PubMed

Langston, Victoria; Gould, Matthew; Greenberg, Neil

2007-09-01

Culture provides the unwritten rules that inform and shape expected behaviors. To date, little research has been conducted into the attitudes or opinions that service personnel hold toward mental health issues. This article examines current literature and research into the recognition of mental health problems in the military and potential organizational barriers to care including stigma and the specific characteristics of a military culture such as the significant reliance on buddy support. We conclude that the barriers to care which operate in both military and civilian populations are not insignificant. Western militaries in fact currently face an uphill struggle to combat the substantial barriers to care that exist.

Self-Recognition Between Two Almost Identical Macroions During Their Assembly: The Effects of pH and Temperature.

PubMed

Haso, Fadi; Li, Dong; Garai, Somenath; Pigga, Joseph M; Liu, Tianbo

2015-09-14

Two Keplerate-type macroions, [Mo(VI) 72 Fe(III) 30 O252 - (CH3 COO)12 {Mo2 O7 (H2 O)}2 {H2 Mo2 O8 (H2 O)}(H2 O)91 ]⋅ca. 150 H2 O= {Mo72 Fe30 } and [{Na(H2 O)12 }⊂{Mo(VI) 72 Cr(III) 30 O252 (CH3 COO)19 - (H2 O)94 }]⋅ca. 120 H2 O={Mo72 Cr30 }, with identical size and shape but different charge density, can self-assemble into spherical "blackberry"-like structures in aqueous solution by means of electrostatic interactions. These two macroanions can self-recognize each other and self-assemble into two separate types of homogeneous blackberries in their mixed dilute aqueous solution, in which they carry -7 and -5 net charges, respectively. Either adjusting the solution pH or raising temperature is expected to make the self-recognition more difficult, by making the charge densities of the two clusters closer, or by decreasing the activation energy barrier for the blackberry formation, respectively. Amazingly, the self-recognition behavior remains, as confirmed by dynamic and static light scattering, TEM, and energy dispersive spectroscopy techniques. The results prove that the self-recognition behavior of the macroions due to the long-range electrostatic interaction is universal and can be achieved when only minimum differences exist between two types of macroanions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hand shape selection in pantomimed grasping: Interaction between the dorsal and the ventral visual streams and convergence on the ventral premotor area

PubMed Central

Makuuchi, Michiru; Someya, Yoshiaki; Ogawa, Seiji; Takayama, Yoshihiro

2011-01-01

In visually guided grasping, possible hand shapes are computed from the geometrical features of the object, while prior knowledge about the object and the goal of the action influence both the computation and the selection of the hand shape. We investigated the system dynamics of the human brain for the pantomiming of grasping with two aspects accentuated. One is object recognition, with the use of objects for daily use. The subjects mimed grasping movements appropriate for an object presented in a photograph either by precision or power grip. The other is the selection of grip hand shape. We manipulated the selection demands for the grip hand shape by having the subjects use the same or different grip type in the second presentation of the identical object. Effective connectivity analysis revealed that the increased selection demands enhance the interaction between the anterior intraparietal sulcus (AIP) and posterior inferior temporal gyrus (pITG), and drive the converging causal influences from the AIP, pITG, and dorsolateral prefrontal cortex to the ventral premotor area (PMv). These results suggest that the dorsal and ventral visual areas interact in the pantomiming of grasping, while the PMv integrates the neural information of different regions to select the hand posture. The present study proposes system dynamics in visually guided movement toward meaningful objects, but further research is needed to examine if the same dynamics is found also in real grasping. PMID:21739528

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis.

PubMed

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3-10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception.

Effects of Steady-State Noise on Verbal Working Memory in Young Adults

PubMed Central

Alt, Mary; DeDe, Gayle; Olson, Sarah; Shehorn, James

2015-01-01

Purpose We set out to examine the impact of perceptual, linguistic, and capacity demands on performance of verbal working-memory tasks. The Ease of Language Understanding model (Rönnberg et al., 2013) provides a framework for testing the dynamics of these interactions within the auditory-cognitive system. Methods Adult native speakers of English (n = 45) participated in verbal working-memory tasks requiring processing and storage of words involving different linguistic demands (closed/open set). Capacity demand ranged from 2 to 7 words per trial. Participants performed the tasks in quiet and in speech-spectrum-shaped noise. Separate groups of participants were tested at different signal-to-noise ratios. Word-recognition measures were obtained to determine effects of noise on intelligibility. Results Contrary to predictions, steady-state noise did not have an adverse effect on working-memory performance in every situation. Noise negatively influenced performance for the task with high linguistic demand. Of particular importance is the finding that the adverse effects of background noise were not confined to conditions involving declines in recognition. Conclusions Perceptual, linguistic, and cognitive demands can dynamically affect verbal working-memory performance even in a population of healthy young adults. Results suggest that researchers and clinicians need to carefully analyze task demands to understand the independent and combined auditory-cognitive factors governing performance in everyday listening situations. PMID:26384291

Recognition of building group patterns in topographic maps based on graph partitioning and random forest

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

Place recognition and heading retrieval are mediated by dissociable cognitive systems in mice.

PubMed

Julian, Joshua B; Keinath, Alexander T; Muzzio, Isabel A; Epstein, Russell A

2015-05-19

A lost navigator must identify its current location and recover its facing direction to restore its bearings. We tested the idea that these two tasks--place recognition and heading retrieval--might be mediated by distinct cognitive systems in mice. Previous work has shown that numerous species, including young children and rodents, use the geometric shape of local space to regain their sense of direction after disorientation, often ignoring nongeometric cues even when they are informative. Notably, these experiments have almost always been performed in single-chamber environments in which there is no ambiguity about place identity. We examined the navigational behavior of mice in a two-chamber paradigm in which animals had to both recognize the chamber in which they were located (place recognition) and recover their facing direction within that chamber (heading retrieval). In two experiments, we found that mice used nongeometric features for place recognition, but simultaneously failed to use these same features for heading retrieval, instead relying exclusively on spatial geometry. These results suggest the existence of separate systems for place recognition and heading retrieval in mice that are differentially sensitive to geometric and nongeometric cues. We speculate that a similar cognitive architecture may underlie human navigational behavior.

Multimodal biometric method that combines veins, prints, and shape of a finger

NASA Astrophysics Data System (ADS)

Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Kim, Jeong Nyeo

2011-01-01

Multimodal biometrics provides high recognition accuracy and population coverage by using various biometric features. A single finger contains finger veins, fingerprints, and finger geometry features; by using multimodal biometrics, information on these multiple features can be simultaneously obtained in a short time and their fusion can outperform the use of a single feature. This paper proposes a new finger recognition method based on the score-level fusion of finger veins, fingerprints, and finger geometry features. This research is novel in the following four ways. First, the performances of the finger-vein and fingerprint recognition are improved by using a method based on a local derivative pattern. Second, the accuracy of the finger geometry recognition is greatly increased by combining a Fourier descriptor with principal component analysis. Third, a fuzzy score normalization method is introduced; its performance is better than the conventional Z-score normalization method. Fourth, finger-vein, fingerprint, and finger geometry recognitions are combined by using three support vector machines and a weighted SUM rule. Experimental results showed that the equal error rate of the proposed method was 0.254%, which was lower than those of the other methods.

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

Target recognition and phase acquisition by using incoherent digital holographic imaging

NASA Astrophysics Data System (ADS)

Lee, Munseob; Lee, Byung-Tak

2017-05-01

In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach

PubMed Central

Ahmad, Riaz; Naz, Saeeda; Afzal, Muhammad Zeshan; Amin, Sayed Hassan; Breuel, Thomas

2015-01-01

The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems. Recognition of the large number of ligatures is often a complicated task in oriental languages such as Pashto, Urdu, Persian and Arabic. Research on cursive script recognition often ignores the fact that scaling, orientation, location and font variations are common in printed cursive text. Therefore, these variations are not included in image databases and in experimental evaluations. This research uncovers challenges faced by Arabic cursive script recognition in a holistic framework by considering Pashto as a test case, because Pashto language has larger alphabet set than Arabic, Persian and Urdu. A database containing 8000 images of 1000 unique ligatures having scaling, orientation and location variations is introduced. In this article, a feature space based on scale invariant feature transform (SIFT) along with a segmentation framework has been proposed for overcoming the above mentioned challenges. The experimental results show a significantly improved performance of proposed scheme over traditional feature extraction techniques such as principal component analysis (PCA). PMID:26368566

Iris Recognition Using Feature Extraction of Box Counting Fractal Dimension

NASA Astrophysics Data System (ADS)

Khotimah, C.; Juniati, D.

2018-01-01

Biometrics is a science that is now growing rapidly. Iris recognition is a biometric modality which captures a photo of the eye pattern. The markings of the iris are distinctive that it has been proposed to use as a means of identification, instead of fingerprints. Iris recognition was chosen for identification in this research because every human has a special feature that each individual is different and the iris is protected by the cornea so that it will have a fixed shape. This iris recognition consists of three step: pre-processing of data, feature extraction, and feature matching. Hough transformation is used in the process of pre-processing to locate the iris area and Daugman’s rubber sheet model to normalize the iris data set into rectangular blocks. To find the characteristics of the iris, it was used box counting method to get the fractal dimension value of the iris. Tests carried out by used k-fold cross method with k = 5. In each test used 10 different grade K of K-Nearest Neighbor (KNN). The result of iris recognition was obtained with the best accuracy was 92,63 % for K = 3 value on K-Nearest Neighbor (KNN) method.

Representation of Glossy Material Surface in Ventral Superior Temporal Sulcal Area of Common Marmosets

PubMed Central

Miyakawa, Naohisa; Banno, Taku; Abe, Hiroshi; Tani, Toshiki; Suzuki, Wataru; Ichinohe, Noritaka

2017-01-01

The common marmoset (Callithrix jacchus) is one of the smallest species of primates, with high visual recognition abilities that allow them to judge the identity and quality of food and objects in their environment. To address the cortical processing of visual information related to material surface features in marmosets, we presented a set of stimuli that have identical three-dimensional shapes (bone, torus or amorphous) but different material appearances (ceramic, glass, fur, leather, metal, stone, wood, or matte) to anesthetized marmoset, and recorded multiunit activities from an area ventral to the superior temporal sulcus (STS) using multi-shanked, and depth resolved multi-electrode array. Out of 143 visually responsive multiunits recorded from four animals, 29% had significant main effect only of the material, 3% only of the shape and 43% of both the material and the shape. Furthermore, we found neuronal cluster(s), in which most cells: (1) showed a significant main effect in material appearance; (2) the best stimulus was a glossy material (glass or metal); and (3) had reduced response to the pixel-shuffled version of the glossy material images. The location of the gloss-selective area was in agreement with previous macaque studies, showing activation in the ventral bank of STS. Our results suggest that perception of gloss is an important ability preserved across wide range of primate species. PMID:28367117

Representation of Glossy Material Surface in Ventral Superior Temporal Sulcal Area of Common Marmosets.

PubMed

Miyakawa, Naohisa; Banno, Taku; Abe, Hiroshi; Tani, Toshiki; Suzuki, Wataru; Ichinohe, Noritaka

2017-01-01

The common marmoset ( Callithrix jacchus ) is one of the smallest species of primates, with high visual recognition abilities that allow them to judge the identity and quality of food and objects in their environment. To address the cortical processing of visual information related to material surface features in marmosets, we presented a set of stimuli that have identical three-dimensional shapes (bone, torus or amorphous) but different material appearances (ceramic, glass, fur, leather, metal, stone, wood, or matte) to anesthetized marmoset, and recorded multiunit activities from an area ventral to the superior temporal sulcus (STS) using multi-shanked, and depth resolved multi-electrode array. Out of 143 visually responsive multiunits recorded from four animals, 29% had significant main effect only of the material, 3% only of the shape and 43% of both the material and the shape. Furthermore, we found neuronal cluster(s), in which most cells: (1) showed a significant main effect in material appearance; (2) the best stimulus was a glossy material (glass or metal); and (3) had reduced response to the pixel-shuffled version of the glossy material images. The location of the gloss-selective area was in agreement with previous macaque studies, showing activation in the ventral bank of STS. Our results suggest that perception of gloss is an important ability preserved across wide range of primate species.

2D Affine and Projective Shape Analysis.

PubMed

Bryner, Darshan; Klassen, Eric; Huiling Le; Srivastava, Anuj

2014-05-01

Current techniques for shape analysis tend to seek invariance to similarity transformations (rotation, translation, and scale), but certain imaging situations require invariance to larger groups, such as affine or projective groups. Here we present a general Riemannian framework for shape analysis of planar objects where metrics and related quantities are invariant to affine and projective groups. Highlighting two possibilities for representing object boundaries-ordered points (or landmarks) and parameterized curves-we study different combinations of these representations (points and curves) and transformations (affine and projective). Specifically, we provide solutions to three out of four situations and develop algorithms for computing geodesics and intrinsic sample statistics, leading up to Gaussian-type statistical models, and classifying test shapes using such models learned from training data. In the case of parameterized curves, we also achieve the desired goal of invariance to re-parameterizations. The geodesics are constructed by particularizing the path-straightening algorithm to geometries of current manifolds and are used, in turn, to compute shape statistics and Gaussian-type shape models. We demonstrate these ideas using a number of examples from shape and activity recognition.

Visual shape perception as Bayesian inference of 3D object-centered shape representations.

PubMed

Erdogan, Goker; Jacobs, Robert A

2017-11-01

Despite decades of research, little is known about how people visually perceive object shape. We hypothesize that a promising approach to shape perception is provided by a "visual perception as Bayesian inference" framework which augments an emphasis on visual representation with an emphasis on the idea that shape perception is a form of statistical inference. Our hypothesis claims that shape perception of unfamiliar objects can be characterized as statistical inference of 3D shape in an object-centered coordinate system. We describe a computational model based on our theoretical framework, and provide evidence for the model along two lines. First, we show that, counterintuitively, the model accounts for viewpoint-dependency of object recognition, traditionally regarded as evidence against people's use of 3D object-centered shape representations. Second, we report the results of an experiment using a shape similarity task, and present an extensive evaluation of existing models' abilities to account for the experimental data. We find that our shape inference model captures subjects' behaviors better than competing models. Taken as a whole, our experimental and computational results illustrate the promise of our approach and suggest that people's shape representations of unfamiliar objects are probabilistic, 3D, and object-centered. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Effects of Pictorial Cues on Reaching Depend on the Distinctiveness of Target Objects

PubMed Central

Himmelbach, Marc

2013-01-01

There is an ongoing debate under what conditions learned object sizes influence visuomotor control under preserved stereovision. Using meaningful objects (matchboxes of locally well-known brands in the UK) a previous study has nicely shown that the recognition of these objects influences action programming by means of reach amplitude and grasp pre-shaping even under binocular vision. Using the same paradigm, we demonstrated that short-term learning of colour-size associations was not sufficient to induce any visuomotor effects under binocular viewing conditions. Now we used the same matchboxes, for which the familiarity effect was shown in the UK, with German participants who have never seen these objects before. We addressed the question whether simply a high degree of distinctness, or whether instead actual prior familiarity of these objects, are required to affect motor computations. We found that under monocular and binocular viewing conditions the learned size and location influenced the amplitude of the reaching component significantly. In contrast, the maximum grip aperture remained unaffected for binocular vision. We conclude that visual distinctness is sufficient to form reliable associations in short-term learning to influence reaching even for preserved stereovision. Grasp pre-shaping instead seems to be less susceptible to such perceptual effects. PMID:23382882

Thermodynamics of Nucleic Acid ‘Shape Readout’ by an Aminosugar†

PubMed Central

Xi, Hongjuan; Davis, Erik; Ranjan, Nihar; Xue, Liang; Hyde-Volpe, David; Arya, Dev P.

2012-01-01

Recognition of nucleic acids is important for our understanding of nucleic acid structure as well as for our understanding of nucleic acid-protein interactions. In addition to the direct readout mechanisms of nucleic acids such as H-bonding, shape recognition of nucleic acids is being increasingly recognized to play an equally important role in DNA recognition. Competition Dialysis, UV, Flourescent Intercalator displacement (FID), Computational Docking, and calorimetry studies were conducted to study the interaction of neomycin with a variety of nucleic acid conformations (shapes). At pH 5.5, these results suggest: (1) Neomycin binds three RNA structures (16S A site rRNA, poly(rA)•poly(rA), and poly(rA)•poly(rU)) with high affinities, Ka~107M−1. (2) The binding of neomycin to A-form GC-rich oligomer d(A2G15C15T2)2 has comparable affinity to RNA structures. (3) The binding of neomycin to DNA•RNA hybrids shows a three-fold variance attributable to their structural differences (poly(dA) •poly(rU), Ka=9.4×106M−1 and poly(rA)•poly(dT), Ka=3.1×106M−1). (4) The interaction of neomycin with DNA triplex poly(dA)•2poly(dT) yields a binding affinity of Ka=2.4×105M−1. (5) Poly(dA-dT)2 showed the lowest association constant for all nucleic acids studied (Ka=<105). (6) Neomycin binds to G-quadruplexes with Ka~104-105M−1. (7) Computational studies show that the decrease in major groove width in the B to A transition correlates with increasing neomycin affinity. Neomycin’s affinity for various nucleic acid structures can be ranked as follows, RNAs and GC-rich d(A2G15C15T2)2 structures > poly(dA)•poly(rU) > poly(rA)•poly(dT) > T•A-T triplex , G-quadruplexes, B-form AT-rich or GC-rich DNA sequences. The results illustrate the first example of a small molecule based ‘shape readout’ of different nucleic acid conformations. PMID:21863895

Ingredients of the Eddy Soup: A Geometric Decomposition of Eddy-Mean Flow Interactions

NASA Astrophysics Data System (ADS)

Waterman, S.; Lilly, J. M.

2014-12-01

Understanding eddy-mean flow interactions is a long-standing problem in geophysical fluid dynamics with modern relevance to the task of representing eddy effects in coarse resolution models while preserving their dependence on the underlying dynamics of the flow field. Exploiting the recognition that the velocity covariance matrix/eddy stress tensor that describes eddy fluxes, also encodes information about eddy size, shape and orientation through its geometric representation in the form of the so-called variance ellipse, suggests a potentially fruitful way forward. Here we present a new framework that describes eddy-mean flow interactions in terms of a geometric description of the eddy motion, and illustrate it with an application to an unstable jet. Specifically we show that the eddy vorticity flux divergence F, a key dynamical quantity describing the average effect of fluctuations on the time-mean flow, may be decomposed into two components with distinct geometric interpretations: 1. variations in variance ellipse orientation; and 2. variations in the anisotropic part of the eddy kinetic energy, a function of the variance ellipse size and shape. Application of the divergence theorem shows that F integrated over a region is explained entirely by variations in these two quantities around the region's periphery. This framework has the potential to offer new insights into eddy-mean flow interactions in a number of ways. It identifies the ingredients of the eddy motion that have a mean flow forcing effect, it links eddy effects to spatial patterns of variance ellipse geometry that can suggest the mechanisms underpinning these effects, and finally it illustrates the importance of resolving eddy shape and orientation, and not just eddy size/energy, to accurately represent eddy feedback effects. These concepts will be both discussed and illustrated.

A Biosocial Developmental Model of Borderline Personality: Elaborating and Extending Linehan's Theory

ERIC Educational Resources Information Center

Crowell, Sheila E.; Beauchaine, Theodore P.; Linehan, Marsha M.

2009-01-01

Over the past several decades, research has focused increasingly on developmental precursors to psychological disorders that were previously assumed to emerge only in adulthood. This change in focus follows from the recognition that complex transactions between biological vulnerabilities and psychosocial risk factors shape emotional and behavioral…

Visualisation of Lines of Best Fit

ERIC Educational Resources Information Center

Rudziewicz, Michael; Bossé, Michael J.; Marland, Eric S.; Rhoads, Gregory S.

2017-01-01

Humans possess a remarkable ability to recognise both simple patterns such as shapes and handwriting and very complex patterns such as faces and landscapes. To investigate one small aspect of human pattern recognition, in this study participants position lines of "best fit" to two-dimensional scatter plots of data. The study investigates…

All Quiet on the (Post) Western Front?

ERIC Educational Resources Information Center

Orwin, Clifford

1996-01-01

Considers multiculturalism within the college environment and the collaborating factors that help shape the mood on campus. The author examines what multiculturalism is, discusses its politics, and explores what it demands of the university in terms of equal recognition and how it encroaches on academic freedom. Final comments highlight…

Similarity and Congruence.

ERIC Educational Resources Information Center

Herman, Daniel L.

This instructional unit is an introduction to the common properties of similarity and congruence. Manipulation of objects leads to a recognition of these properties. The ASA, SAS, and SSS theorems are not mentioned. Limited use is made in the application of the properties of size and shape preserved by similarity or congruence. A teacher's guide…

Communication in a Divided World: Opportunities and Constraints.

ERIC Educational Resources Information Center

Lasswell, Harold

Communication systems in a divided world can perpetuate tension and violence or can be instrumental in developing unity. In response to this power, communicators must focus on generating worldwide recognition of interdependence in the shaping and sharing of values. Likewise, a responsible communication policy must stimulate the invention and…

Bayesian Methods and Confidence Intervals for Automatic Target Recognition of SAR Canonical Shapes

DTIC Science & Technology

2014-03-27

and DirectX [22]. The CUDA platform was developed by the NVIDIA Corporation to allow programmers access to the computational capabilities of the...were used for the intense repetitive computations. Developing CUDA software requires writing code for specialized compilers provided by NVIDIA and

Writing and Rhetoric Majors, Disciplinarity, and "Techne"

ERIC Educational Resources Information Center

Scott, J. Blake; Meloncon, Lisa

2017-01-01

How we argue for, create, and mobilize around writing and rhetoric majors will continue to shape our field's disciplinarity in crucial ways, including our recognition, resources, and relationships. The range of such majors and their institutional contexts, and the disparate field-level efforts to track and build consensus around them, generate…

"Teacher You Are Stupid!"--Cultivating a Reflective Disposition

ERIC Educational Resources Information Center

Farrell, Thomas S. C.

2014-01-01

There is a longstanding recognition in the field of language education that teachers must continually shape and reshape their knowledge of teaching and learning throughout their careers (Farrell, 2015). Much of a teacher's early knowledge is developed initially in teacher education programs, and then through teaching experiences and…

Implicit Multisensory Associations Influence Voice Recognition

PubMed Central

von Kriegstein, Katharina; Giraud, Anne-Lise

2006-01-01

Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules. PMID:17002519

Medical image segmentation by combining graph cuts and oriented active appearance models.

PubMed

Chen, Xinjian; Udupa, Jayaram K; Bagci, Ulas; Zhuge, Ying; Yao, Jianhua

2012-04-01

In this paper, we propose a novel method based on a strategic combination of the active appearance model (AAM), live wire (LW), and graph cuts (GCs) for abdominal 3-D organ segmentation. The proposed method consists of three main parts: model building, object recognition, and delineation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the recognition part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW methods, resulting in the oriented AAM (OAAM). A multiobject strategy is utilized to help in object initialization. We employ a pseudo-3-D initialization strategy and segment the organs slice by slice via a multiobject OAAM method. For the object delineation part, a 3-D shape-constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT data set and also on the MICCAI 2007 Grand Challenge liver data set. The results show the following: 1) The overall segmentation accuracy of true positive volume fraction TPVF > 94.3% and false positive volume fraction can be achieved; 2) the initialization performance can be improved by combining the AAM and LW; 3) the multiobject strategy greatly facilitates initialization; 4) compared with the traditional 3-D AAM method, the pseudo-3-D OAAM method achieves comparable performance while running 12 times faster; and 5) the performance of the proposed method is comparable to state-of-the-art liver segmentation algorithm. The executable version of the 3-D shape-constrained GC method with a user interface can be downloaded from http://xinjianchen.wordpress.com/research/.

Living with disasters: social capital for disaster governance.

PubMed

Melo Zurita, Maria de Lourdes; Cook, Brian; Thomsen, Dana C; Munro, Paul G; Smith, Timothy F; Gallina, John

2017-10-24

This paper explores how social networks and bonds within and across organisations shape disaster operations and strategies. Local government disaster training exercises serve as a window through which to view these relations, and 'social capital' is used as an analytic for making sense of the human relations at the core of disaster management operations. These elements help to expose and substantiate the often intangible relations that compose the culture that exists, and that is shaped by preparations for disasters. The study reveals how this social capital has been generated through personal interactions, which are shared among disaster managers across different organisations and across 'levels' within those organisations. Recognition of these 'group resources' has significant implications for disaster management in which conducive social relations have become paramount. The paper concludes that socio-cultural relations, as well as a people-centred approach to preparations, appear to be effective means of readying for, and ultimately responding to, disasters. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

The shape of the face template: geometric distortions of faces and their detection in natural scenes.

PubMed

Pongakkasira, Kaewmart; Bindemann, Markus

2015-04-01

Human face detection might be driven by skin-coloured face-shaped templates. To explore this idea, this study compared the detection of faces for which the natural height-to-width ratios were preserved with distorted faces that were stretched vertically or horizontally. The impact of stretching on detection performance was not obvious when faces were equated to their unstretched counterparts in terms of their height or width dimension (Experiment 1). However, stretching impaired detection when the original and distorted faces were matched for their surface area (Experiment 2), and this was found with both vertically and horizontally stretched faces (Experiment 3). This effect was evident in accuracy, response times, and also observers' eye movements to faces. These findings demonstrate that height-to-width ratios are an important component of the cognitive template for face detection. The results also highlight important differences between face detection and face recognition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Transfer-appropriate processing in recognition memory: perceptual and conceptual effects on recognition memory depend on task demands.

PubMed

Parks, Colleen M

2013-07-01

Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which suggest that the extent to which perceptual fluency matters on a recognition test depends in large part on the task demands. A test that recruits perceptual processing for discrimination should show greater perceptual effects and smaller conceptual effects than standard recognition, similar to the pattern of effects found in perceptual implicit memory tasks. This idea was tested in the current experiment by crossing a levels of processing manipulation with a modality manipulation on a series of recognition tests that ranged from conceptual (standard recognition) to very perceptually demanding (a speeded recognition test with degraded stimuli). Results showed that the levels of processing effect decreased and the effect of modality increased when tests were made perceptually demanding. These results support the idea that surface-level features influence performance on recognition tests when they are made salient by the task demands. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Relative contributions of acoustic temporal fine structure and envelope cues for lexical tone perception in noise

PubMed Central

Qi, Beier; Mao, Yitao; Liu, Jiaxing; Liu, Bo; Xu, Li

2017-01-01

Previous studies have shown that lexical tone perception in quiet relies on the acoustic temporal fine structure (TFS) but not on the envelope (E) cues. The contributions of TFS to speech recognition in noise are under debate. In the present study, Mandarin tone tokens were mixed with speech-shaped noise (SSN) or two-talker babble (TTB) at five signal-to-noise ratios (SNRs; −18 to +6 dB). The TFS and E were then extracted from each of the 30 bands using Hilbert transform. Twenty-five combinations of TFS and E from the sound mixtures of the same tone tokens at various SNRs were created. Twenty normal-hearing, native-Mandarin-speaking listeners participated in the tone-recognition test. Results showed that tone-recognition performance improved as the SNRs in either TFS or E increased. The masking effects on tone perception for the TTB were weaker than those for the SSN. For both types of masker, the perceptual weights of TFS and E in tone perception in noise was nearly equivalent, with E playing a slightly greater role than TFS. Thus, the relative contributions of TFS and E cues to lexical tone perception in noise or in competing-talker maskers differ from those in quiet and those to speech perception of non-tonal languages. PMID:28599529

Assessing the Importance of Lexical Tone Contour to Sentence Perception in Mandarin-Speaking Children With Normal Hearing.

PubMed

Zhu, Shufeng; Wong, Lena L N; Wang, Bin; Chen, Fei

2017-07-12

The aim of the present study was to evaluate the influence of lexical tone contour and age on sentence perception in quiet and in noise conditions in Mandarin-speaking children ages 7 to 11 years with normal hearing. Test materials were synthesized Mandarin sentences, each word with a manipulated lexical contour, that is, normal contour, flat contour, or a tone contour randomly selected from the four Mandarin lexical tone contours. A convenience sample of 75 Mandarin-speaking participants with normal hearing, ages 7, 9, and 11 years (25 participants in each age group), was selected. Participants were asked to repeat the synthesized speech in quiet and in speech spectrum-shaped noise at 0 dB signal-to-noise ratio. In quiet, sentence recognition by the 11-year-old children was similar to that of adults, and misrepresented lexical tone contours did not have a detrimental effect. However, the performance of children ages 9 and 7 years was significantly poorer. The performance of all three age groups, especially the younger children, declined significantly in noise. The present research suggests that lexical tone contour plays an important role in Mandarin sentence recognition, and misrepresented tone contours result in greater difficulty in sentence recognition in younger children. These results imply that maturation and/or language use experience play a role in the processing of tone contours for Mandarin speech understanding, particularly in noise.

Probing the interaction of archaeal DNA polymerases with deaminated bases using X-ray crystallography and non-hydrogen bonding isosteric base analogues.

PubMed

Killelea, Tom; Ghosh, Samantak; Tan, Samuel S; Heslop, Pauline; Firbank, Susan J; Kool, Eric T; Connolly, Bernard A

2010-07-13

Archaeal family-B DNA polymerases stall replication on encountering the pro-mutagenic bases uracil and hypoxanthine. This publication describes an X-ray crystal structure of Thermococcus gorgonarius polymerase in complex with a DNA containing hypoxanthine in the single-stranded region of the template, two bases ahead of the primer-template junction. Full details of the specific recognition of hypoxanthine are revealed, allowing a comparison with published data that describe uracil binding. The two bases are recognized by the same pocket, in the N-terminal domain, and make very similar protein-DNA interactions. Specificity for hypoxanthine (and uracil) arises from a combination of polymerase-base hydrogen bonds and shape fit between the deaminated bases and the pocket. The structure with hypoxanthine at position 2 explains the stimulation of the polymerase 3'-5' proofreading exonuclease, observed with deaminated bases at this location. A beta-hairpin element, involved in partitioning the primer strand between the polymerase and exonuclease active sites, inserts between the two template bases at the extreme end of the double-stranded DNA. This denatures the two complementary primer bases and directs the resulting 3' single-stranded extension toward the exonuclease active site. Finally, the relative importance of hydrogen bonding and shape fit in determining selectivity for deaminated bases has been examined using nonpolar isosteres. Affinity for both 2,4-difluorobenzene and fluorobenzimidazole, non-hydrogen bonding shape mimics of uracil and hypoxanthine, respectively, is strongly diminished, suggesting polar protein-base contacts are important. However, residual interaction with 2,4-difluorobenzene is seen, confirming a role for shape recognition.

Shy children are less sensitive to some cues to facial recognition.

PubMed

Brunet, Paul M; Mondloch, Catherine J; Schmidt, Louis A

2010-02-01

Temperamental shyness in children is characterized by avoidance of faces and eye contact, beginning in infancy. We conducted two studies to determine whether temperamental shyness was associated with deficits in sensitivity to some cues to facial identity. In Study 1, 40 typically developing 10-year-old children made same/different judgments about pairs of faces that differed in the appearance of individual features, the shape of the external contour, or the spacing among features; their parent completed the Colorado childhood temperament inventory (CCTI). Children who scored higher on CCTI shyness made more errors than their non-shy counterparts only when discriminating faces based on the spacing of features. Differences in accuracy were not related to other scales of the CCTI. In Study 2, we showed that these differences were face-specific and cannot be attributed to differences in task difficulty. Findings suggest that shy children are less sensitive to some cues to facial recognition possibly underlying their inability to distinguish certain facial emotions in others, leading to a cascade of secondary negative effects in social behaviour.

Protein Camouflage: Supramolecular Anion Recognition by Ubiquitin.

PubMed

Mallon, Madeleine; Dutt, Som; Schrader, Thomas; Crowley, Peter B

2016-04-15

Progress in the field of bio-supramolecular chemistry, the bottom-up assembly of protein-ligand systems, relies on a detailed knowledge of molecular recognition. To address this issue, we have characterised complex formation between human ubiquitin (HUb) and four supramolecular anions. The ligands were: pyrenetetrasulfonic acid (4PSA), p-sulfonato-calix[4]arene (SCLX4), bisphosphate tweezers (CLR01) and meso-tetrakis (4-sulfonatophenyl)porphyrin (TPPS), which vary in net charge, size, shape and hydrophobicity. All four ligands induced significant changes in the HSQC spectrum of HUb. Chemical shift perturbations and line-broadening effects were used to identify binding sites and to quantify affinities. Supporting data were obtained from docking simulations. It was found that these weakly interacting ligands bind to extensive surface patches on HUb. A comparison of the data suggests some general indicators for the protein-binding specificity of supramolecular anions. Differences in binding were observed between the cavity-containing and planar ligands. The former had a preference for the arginine-rich, flexible C terminus of HUb. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

Interplay between affect and arousal in recognition memory.

PubMed

Greene, Ciara M; Bahri, Pooja; Soto, David

2010-07-23

Emotional states linked to arousal and mood are known to affect the efficiency of cognitive performance. However, the extent to which memory processes may be affected by arousal, mood or their interaction is poorly understood. Following a study phase of abstract shapes, we altered the emotional state of participants by means of exposure to music that varied in both mood and arousal dimensions, leading to four different emotional states: (i) positive mood-high arousal; (ii) positive mood-low arousal; (iii) negative mood-high arousal; (iv) negative mood-low arousal. Following the emotional induction, participants performed a memory recognition test. Critically, there was an interaction between mood and arousal on recognition performance. Memory was enhanced in the positive mood-high arousal and in the negative mood-low arousal states, relative to the other emotional conditions. Neither mood nor arousal alone but their interaction appears most critical to understanding the emotional enhancement of memory.

Programmable molecular recognition based on the geometry of DNA nanostructures.

PubMed

Woo, Sungwook; Rothemund, Paul W K

2011-07-10

From ligand-receptor binding to DNA hybridization, molecular recognition plays a central role in biology. Over the past several decades, chemists have successfully reproduced the exquisite specificity of biomolecular interactions. However, engineering multiple specific interactions in synthetic systems remains difficult. DNA retains its position as the best medium with which to create orthogonal, isoenergetic interactions, based on the complementarity of Watson-Crick binding. Here we show that DNA can be used to create diverse bonds using an entirely different principle: the geometric arrangement of blunt-end stacking interactions. We show that both binary codes and shape complementarity can serve as a basis for such stacking bonds, and explore their specificity, thermodynamics and binding rules. Orthogonal stacking bonds were used to connect five distinct DNA origami. This work, which demonstrates how a single attractive interaction can be developed to create diverse bonds, may guide strategies for molecular recognition in systems beyond DNA nanostructures.

Structural evolution of glycan recognition by a family of potent HIV antibodies.

PubMed

Garces, Fernando; Sok, Devin; Kong, Leopold; McBride, Ryan; Kim, Helen J; Saye-Francisco, Karen F; Julien, Jean-Philippe; Hua, Yuanzi; Cupo, Albert; Moore, John P; Paulson, James C; Ward, Andrew B; Burton, Dennis R; Wilson, Ian A

2014-09-25

The HIV envelope glycoprotein (Env) is densely covered with self-glycans that should help shield it from recognition by the human immune system. Here, we examine how a particularly potent family of broadly neutralizing antibodies (Abs) has evolved common and distinct structural features to counter the glycan shield and interact with both glycan and protein components of HIV Env. The inferred germline antibody already harbors potential binding pockets for a glycan and a short protein segment. Affinity maturation then leads to divergent evolutionary branches that either focus on a single glycan and protein segment (e.g., Ab PGT124) or engage multiple glycans (e.g., Abs PGT121-123). Furthermore, other surrounding glycans are avoided by selecting an appropriate initial antibody shape that prevents steric hindrance. Such molecular recognition lessons are important for engineering proteins that can recognize or accommodate glycans. Copyright © 2014 Elsevier Inc. All rights reserved.

New approach for segmentation and recognition of handwritten numeral strings

NASA Astrophysics Data System (ADS)

Sadri, Javad; Suen, Ching Y.; Bui, Tien D.

2004-12-01

In this paper, we propose a new system for segmentation and recognition of unconstrained handwritten numeral strings. The system uses a combination of foreground and background features for segmentation of touching digits. The method introduces new algorithms for traversing the top/bottom-foreground-skeletons of the touched digits, and for finding feature points on these skeletons, and matching them to build all the segmentation paths. For the first time a genetic representation is used to show all the segmentation hypotheses. Our genetic algorithm tries to search and evolve the population of candidate segmentations and finds the one with the highest confidence for its segmentation and recognition. We have also used a new method for feature extraction which lowers the variations in the shapes of the digits, and then a MLP neural network is utilized to produce the labels and confidence values for those digits. The NIST SD19 and CENPARMI databases are used for evaluating the system. Our system can get a correct segmentation-recognition rate of 96.07% with rejection rate of 2.61% which compares favorably with those that exist in the literature.

New approach for segmentation and recognition of handwritten numeral strings

NASA Astrophysics Data System (ADS)

Sadri, Javad; Suen, Ching Y.; Bui, Tien D.

2005-01-01

In this paper, we propose a new system for segmentation and recognition of unconstrained handwritten numeral strings. The system uses a combination of foreground and background features for segmentation of touching digits. The method introduces new algorithms for traversing the top/bottom-foreground-skeletons of the touched digits, and for finding feature points on these skeletons, and matching them to build all the segmentation paths. For the first time a genetic representation is used to show all the segmentation hypotheses. Our genetic algorithm tries to search and evolve the population of candidate segmentations and finds the one with the highest confidence for its segmentation and recognition. We have also used a new method for feature extraction which lowers the variations in the shapes of the digits, and then a MLP neural network is utilized to produce the labels and confidence values for those digits. The NIST SD19 and CENPARMI databases are used for evaluating the system. Our system can get a correct segmentation-recognition rate of 96.07% with rejection rate of 2.61% which compares favorably with those that exist in the literature.

Global RNA Fold and Molecular Recognition for a pfl Riboswitch Bound to ZMP, a Master Regulator of One-Carbon Metabolism

DOE PAGES

Ren, Aiming; Rajashankar, Kanagalaghatta R.; Patel, Dinshaw J.

2015-06-25

ZTP, the pyrophosphorylated analog of ZMP (5- amino-4-imidazole carboxamide ribose-5'-monophosphate), was identified as an alarmone that senses 10-formyl-tetrahydroflate deficiency in bacteria. Recently, a pfl riboswitch was identified that selectively binds ZMP and regulates genes associated with purine biosynthesis and one-carbon metabolism. Here we report on the structure of the ZMP-bound Thermosinus carboxydivorans pfl riboswitch sensing domain, thereby defining the pseudoknot-based tertiary RNA fold, the binding-pocket architecture, and principles underlying ligand recognition specificity. Molecular recognition involves shape complementarity, with the ZMP 5-amino and carboxamide groups paired with the Watson-Crick edge of an invariant uracil, and the imidazole ring sandwiched between guanines,more » while the sugar hydroxyls form intermolecular hydrogen bond contacts. The burial of the ZMP base and ribose moieties, together with unanticipated coordination of the carboxamide by Mg 2+, contrasts with exposure of the 5'-phosphate to solvent. Lastly, our studies highlight the principles underlying RNA-based recognition of ZMP, a master regulator of one-carbon metabolism.« less

Global RNA Fold and Molecular Recognition for a pfl Riboswitch Bound to ZMP, a Master Regulator of One-Carbon Metabolism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Aiming; Rajashankar, Kanagalaghatta R.; Patel, Dinshaw J.

ZTP, the pyrophosphorylated analog of ZMP (5- amino-4-imidazole carboxamide ribose-5'-monophosphate), was identified as an alarmone that senses 10-formyl-tetrahydroflate deficiency in bacteria. Recently, a pfl riboswitch was identified that selectively binds ZMP and regulates genes associated with purine biosynthesis and one-carbon metabolism. Here we report on the structure of the ZMP-bound Thermosinus carboxydivorans pfl riboswitch sensing domain, thereby defining the pseudoknot-based tertiary RNA fold, the binding-pocket architecture, and principles underlying ligand recognition specificity. Molecular recognition involves shape complementarity, with the ZMP 5-amino and carboxamide groups paired with the Watson-Crick edge of an invariant uracil, and the imidazole ring sandwiched between guanines,more » while the sugar hydroxyls form intermolecular hydrogen bond contacts. The burial of the ZMP base and ribose moieties, together with unanticipated coordination of the carboxamide by Mg 2+, contrasts with exposure of the 5'-phosphate to solvent. Lastly, our studies highlight the principles underlying RNA-based recognition of ZMP, a master regulator of one-carbon metabolism.« less

Syntactic/semantic techniques for feature description and character recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, R.C.

1983-01-01

The Pattern Analysis Branch, Mapping, Charting and Geodesy (MC/G) Division, of the Naval Ocean Research and Development Activity (NORDA) has been involved over the past several years in the development of algorithms and techniques for computer recognition of free-form handprinted symbols as they appear on the Defense Mapping Agency (DMA) maps and charts. NORDA has made significant contributions to the automation of MC/G through advancing the state of the art in such information extraction techniques. In particular, new concepts in character (symbol) skeletonization, rugged feature measurements, and expert system-oriented decision logic have allowed the development of a very high performancemore » Handprinted Symbol Recognition (HSR) system for identifying depth soundings from naval smooth sheets (accuracies greater than 99.5%). The study reported in this technical note is part of NORDA's continuing research and development in pattern and shape analysis as it applies to Navy and DMA ocean/environment problems. The issue addressed in this technical note deals with emerging areas of syntactic and semantic techniques in pattern recognition as they might apply to the free-form symbol problem.« less

Comparison of eye imaging pattern recognition using neural network

NASA Astrophysics Data System (ADS)

Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.

2015-05-01

The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.

Animacy and real-world size shape object representations in the human medial temporal lobes.

PubMed

Blumenthal, Anna; Stojanoski, Bobby; Martin, Chris B; Cusack, Rhodri; Köhler, Stefan

2018-06-26

Identifying what an object is, and whether an object has been encountered before, is a crucial aspect of human behavior. Despite this importance, we do not yet have a complete understanding of the neural basis of these abilities. Investigations into the neural organization of human object representations have revealed category specific organization in the ventral visual stream in perceptual tasks. Interestingly, these categories fall within broader domains of organization, with reported distinctions between animate, inanimate large, and inanimate small objects. While there is some evidence for category specific effects in the medial temporal lobe (MTL), in particular in perirhinal and parahippocampal cortex, it is currently unclear whether domain level organization is also present across these structures. To this end, we used fMRI with a continuous recognition memory task. Stimuli were images of objects from several different categories, which were either animate or inanimate, or large or small within the inanimate domain. We employed representational similarity analysis (RSA) to test the hypothesis that object-evoked responses in MTL structures during recognition-memory judgments also show evidence for domain-level organization along both dimensions. Our data support this hypothesis. Specifically, object representations were shaped by either animacy, real-world size, or both, in perirhinal and parahippocampal cortex, and the hippocampus. While sensitivity to these dimensions differed across structures when probed individually, hinting at interesting links to functional differentiation, similarities in organization across MTL structures were more prominent overall. These results argue for continuity in the organization of object representations in the ventral visual stream and the MTL. © 2018 Wiley Periodicals, Inc.

Modeling of DNA-Mediated Self-Assembly from Anisotropic Nanoparticles: A Molecular Dynamics Study

NASA Astrophysics Data System (ADS)

Millan, Jaime; Girard, Martin; Brodin, Jeffrey; O'Brien, Matt; Mirkin, Chad; Olvera de La Cruz, Monica

The programmable selectivity of DNA recognition constitutes an elegant scheme to self-assemble a rich variety of superlattices from versatile nanoscale building blocks, where the natural interactions between building blocks are traded by complementary DNA hybridization interactions. Recently, we introduced and validated a scale-accurate coarse-grained model for a molecular dynamics approach that captures the dynamic nature of DNA hybridization events and reproduces the experimentally-observed crystallization behavior of various mixtures of spherical DNA-modified nanoparticles. Here, we have extended this model to robustly reproduce the assembly of nanoparticles with the anisotropic shapes observed experimentally. In particular, we are interested in two different particle types: (i) regular shapes, namely the cubic and octahedral polyhedra shapes commonly observed in gold nanoparticles, and (ii) irregular shapes akin to those exhibited by enzymes. Anisotropy in shape can provide an analog to the atomic orbitals exhibited by conventional atomic crystals. We present results for the assembly of enzymes or anisotropic nanoparticles and the co-assembly of enzymes and nanoparticles.

Superlattices assembled through shape-induced directional binding

NASA Astrophysics Data System (ADS)

Lu, Fang; Yager, Kevin G.; Zhang, Yugang; Xin, Huolin; Gang, Oleg

2015-04-01

Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic spherical nanoparticles via shape-induced directional interactions facilitated by DNA recognition. We show that these polyhedral blocks--cubes and octahedrons--when mixed with spheres, promote the assembly of clusters with architecture determined by polyhedron symmetry. Moreover, three-dimensional binary superlattices are formed when DNA shells accommodate the shape disparity between nanoparticle interfaces. The crystallographic symmetry of assembled lattices is determined by the spatial symmetry of the block's facets, while structural order depends on DNA-tuned interactions and particle size ratio. The presented lattice assembly strategy, exploiting shape for defining the global structure and DNA-mediation locally, opens novel possibilities for by-design fabrication of binary lattices.

Superlattices assembled through shape-induced directional binding

DOE PAGES

Lu, Fang; Yager, Kevin G.; Zhang, Yugang; ...

2015-04-23

Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic spherical nanoparticles via shape-induced directional interactions facilitated by DNA recognition. We show that these polyhedral blocks—cubes and octahedrons—when mixed with spheres, promote the assembly of clusters with architecture determined by polyhedron symmetry. Moreover, three-dimensional binary superlattices are formed when DNA shells accommodate the shape disparity between nanoparticle interfaces. The crystallographic symmetry of assembled lattices is determined bymore » the spatial symmetry of the block’s facets, while structural order depends on DNA-tuned interactions and particle size ratio. Lastly, the presented lattice assembly strategy, exploiting shape for defining the global structure and DNA-mediation locally, opens novel possibilities for by-design fabrication of binary lattices.« less

C60 Recognition from Extended Tetrathiafulvalene Bis-acetylide Platinum(II) Complexes.

PubMed

Bastien, Guillaume; Dron, Paul I; Vincent, Manon; Canevet, David; Allain, Magali; Goeb, Sébastien; Sallé, Marc

2016-11-18

The favorable spatial organization imposed by the square planar 4,4'-di(tert-butyl)-2,2'-bipyridine (dbbpy) platinum(II) complex associated with the electronic and shape complementarity of π-extended tetrathiafulvalene derivatives (exTTF) toward fullerenes is usefully exploited to construct molecular tweezers, which display good affinities for C 60 .

Higher Education, Further Education and the English Experiment

ERIC Educational Resources Information Center

Parry, Gareth

2009-01-01

England has a two-sector system of higher education and further education. Shaped by legislation in 1988 and 1992, the architecture of this system was intended to concentrate each type of education in separate institutions and separate sectors. In recognition of these different missions, each territory came under different funding and regulatory…

Identifying Differences in Early Mathematical Skills among Children in Head Start

ERIC Educational Resources Information Center

Wu, Qiong; Lei, Pui-wa; DiPerna, James C.; Morgan, Paul L.; Reid, Erin E.

2015-01-01

The purpose of this study was to examine early mathematical skill differences among preschool children in US Head Start classrooms. Latent class analysis based on six early mathematical subtest scores (i.e. counting aloud, measurement, counting objects, numbers and shapes, pattern recognition, and grouping) from a sample of 279 Head Start children…

Decolonial Pedagogy and the Ethics of the Global

ERIC Educational Resources Information Center

De Lissovoy, Noah

2010-01-01

An ethical and democratic globality, and the kind of education that would contribute to it, are only possible in the context of a recognition of the relations of power that have shaped history, and in particular the political, cultural, economic, and epistemological processes of domination that have characterized colonialism and Eurocentrism.…

The Changing Influence of Educational Policy and Race on Metropolitan Inequality, 1970-2010

ERIC Educational Resources Information Center

Johnson, Odis, Jr.

2017-01-01

Schools do not receive much recognition within urban sociological research for the role they perform in shaping the demographic, structural, and social features of neighborhoods, cities, and metropolitan areas. In contrast, this article links schools, and the racial avoidance that operates through educational policy, to the extreme economic…

Harnessing Spatial Thinking to Support STEM Learning. OECD Education Working Papers, No. 161

ERIC Educational Resources Information Center

Newcombe, Nora

2017-01-01

Spatial intelligence concerns the locations of objects, their shapes, their relations, and the paths they take as they move. Recognition of spatial skills enriches the traditional educational focus on developing literacy and numerical skills to include a cognitive domain particularly relevant to achievement in science, technology, engineering and…

Teacher as Researcher: Teaching as Lived Research

ERIC Educational Resources Information Center

Binder, Marni

2012-01-01

Teacher inquiry can shape empirical inquiries by nonpracticing researchers, by allowing them to draw on the practical knowledge of those in the classroom. This recognition challenged the author to question what legitimized her role as a teacher-researcher and ask how she could have felt empowered as a researcher without higher education. In this…

Recognizing human actions by learning and matching shape-motion prototype trees.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2012-03-01

A shape-motion prototype-based approach is introduced for action recognition. The approach represents an action as a sequence of prototypes for efficient and flexible action matching in long video sequences. During training, an action prototype tree is learned in a joint shape and motion space via hierarchical K-means clustering and each training sequence is represented as a labeled prototype sequence; then a look-up table of prototype-to-prototype distances is generated. During testing, based on a joint probability model of the actor location and action prototype, the actor is tracked while a frame-to-prototype correspondence is established by maximizing the joint probability, which is efficiently performed by searching the learned prototype tree; then actions are recognized using dynamic prototype sequence matching. Distance measures used for sequence matching are rapidly obtained by look-up table indexing, which is an order of magnitude faster than brute-force computation of frame-to-frame distances. Our approach enables robust action matching in challenging situations (such as moving cameras, dynamic backgrounds) and allows automatic alignment of action sequences. Experimental results demonstrate that our approach achieves recognition rates of 92.86 percent on a large gesture data set (with dynamic backgrounds), 100 percent on the Weizmann action data set, 95.77 percent on the KTH action data set, 88 percent on the UCF sports data set, and 87.27 percent on the CMU action data set.

Selective habituation shapes acoustic predator recognition in harbour seals.

PubMed

Deecke, Volker B; Slater, Peter J B; Ford, John K B

2002-11-14

Predation is a major force in shaping the behaviour of animals, so that precise identification of predators will confer substantial selective advantages on animals that serve as food to others. Because experience with a predator can be lethal, early researchers studying birds suggested that predator recognition does not require learning. However, a predator image that can be modified by learning and experience will be advantageous in situations where cues associated with the predator are highly variable or change over time. In this study, we investigated the response of harbour seals (Phoca vitulina) to the underwater calls of different populations of killer whales (Orcinus orca). We found that the seals responded strongly to the calls of mammal-eating killer whales and unfamiliar fish-eating killer whales but not to the familiar calls of the local fish-eating population. This demonstrates that wild harbour seals are capable of complex acoustic discrimination and that they modify their predator image by selectively habituating to the calls of harmless killer whales. Fear in these animals is therefore focused on local threats by learning and experience.

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

NASA Technical Reports Server (NTRS)

Logan, T. L.; Huning, J. R.; Glackin, D. L.

1983-01-01

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

Anthropomorphic robot for recognition and drawing generalized object images

NASA Astrophysics Data System (ADS)

Ginzburg, Vera M.

1998-10-01

The process of recognition, for instance, understanding the text, written by different fonts, consists in the depriving of the individual attributes of the letters in the particular font. It is shown that such process, in Nature and technique, can be provided by the narrowing the spatial frequency of the object's image by its defocusing. In defocusing images remain only areas, so-called Informative Fragments (IFs), which all together form the generalized (stylized) image of many identical objects. It is shown that the variety of shapes of IFs is restricted and can be presented by `Geometrical alphabet'. The `letters' for this alphabet can be created using two basic `genetic' figures: a stripe and round spot. It is known from physiology that the special cells of visual cortex response to these particular figures. The prototype of such `genetic' alphabet has been made using Boolean algebra (Venn's diagrams). The algorithm for drawing the letter's (`genlet's') shape in this alphabet and generalized images of objects (for example, `sleeping cat'), are given. A scheme of an anthropomorphic robot is shown together with results of model computer experiment of the robot's action--`drawing' the generalized image.

Discriminating Power of Localized Three-Dimensional Facial Morphology

PubMed Central

Hammond, Peter; Hutton, Tim J.; Allanson, Judith E.; Buxton, Bernard; Campbell, Linda E.; Clayton-Smith, Jill; Donnai, Dian; Karmiloff-Smith, Annette; Metcalfe, Kay; Murphy, Kieran C.; Patton, Michael; Pober, Barbara; Prescott, Katrina; Scambler, Pete; Shaw, Adam; Smith, Ann C. M.; Stevens, Angela F.; Temple, I. Karen; Hennekam, Raoul; Tassabehji, May

2005-01-01

Many genetic syndromes involve a facial gestalt that suggests a preliminary diagnosis to an experienced clinical geneticist even before a clinical examination and genotyping are undertaken. Previously, using visualization and pattern recognition, we showed that dense surface models (DSMs) of full face shape characterize facial dysmorphology in Noonan and in 22q11 deletion syndromes. In this much larger study of 696 individuals, we extend the use of DSMs of the full face to establish accurate discrimination between controls and individuals with Williams, Smith-Magenis, 22q11 deletion, or Noonan syndromes and between individuals with different syndromes in these groups. However, the full power of the DSM approach is demonstrated by the comparable discriminating abilities of localized facial features, such as periorbital, perinasal, and perioral patches, and the correlation of DSM-based predictions and molecular findings. This study demonstrates the potential of face shape models to assist clinical training through visualization, to support clinical diagnosis of affected individuals through pattern recognition, and to enable the objective comparison of individuals sharing other phenotypic or genotypic properties. PMID:16380911