Imaging Systems: What, When, How.

ERIC Educational Resources Information Center

Lunin, Lois F.; And Others

1992-01-01

The three articles in this special section on document image files discuss intelligent character recognition, including comparison with optical character recognition; selection of displays for document image processing, focusing on paperlike displays; and imaging hardware, software, and vendors, including guidelines for system selection. (MES)

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.

A comparison study between MLP and convolutional neural network models for character recognition

NASA Astrophysics Data System (ADS)

Ben Driss, S.; Soua, M.; Kachouri, R.; Akil, M.

2017-05-01

Optical Character Recognition (OCR) systems have been designed to operate on text contained in scanned documents and images. They include text detection and character recognition in which characters are described then classified. In the classification step, characters are identified according to their features or template descriptions. Then, a given classifier is employed to identify characters. In this context, we have proposed the unified character descriptor (UCD) to represent characters based on their features. Then, matching was employed to ensure the classification. This recognition scheme performs a good OCR Accuracy on homogeneous scanned documents, however it cannot discriminate characters with high font variation and distortion.3 To improve recognition, classifiers based on neural networks can be used. The multilayer perceptron (MLP) ensures high recognition accuracy when performing a robust training. Moreover, the convolutional neural network (CNN), is gaining nowadays a lot of popularity for its high performance. Furthermore, both CNN and MLP may suffer from the large amount of computation in the training phase. In this paper, we establish a comparison between MLP and CNN. We provide MLP with the UCD descriptor and the appropriate network configuration. For CNN, we employ the convolutional network designed for handwritten and machine-printed character recognition (Lenet-5) and we adapt it to support 62 classes, including both digits and characters. In addition, GPU parallelization is studied to speed up both of MLP and CNN classifiers. Based on our experimentations, we demonstrate that the used real-time CNN is 2x more relevant than MLP when classifying characters.

Maximum mutual information estimation of a simplified hidden MRF for offline handwritten Chinese character recognition

NASA Astrophysics Data System (ADS)

Xiong, Yan; Reichenbach, Stephen E.

1999-01-01

Understanding of hand-written Chinese characters is at such a primitive stage that models include some assumptions about hand-written Chinese characters that are simply false. So Maximum Likelihood Estimation (MLE) may not be an optimal method for hand-written Chinese characters recognition. This concern motivates the research effort to consider alternative criteria. Maximum Mutual Information Estimation (MMIE) is an alternative method for parameter estimation that does not derive its rationale from presumed model correctness, but instead examines the pattern-modeling problem in automatic recognition system from an information- theoretic point of view. The objective of MMIE is to find a set of parameters in such that the resultant model allows the system to derive from the observed data as much information as possible about the class. We consider MMIE for recognition of hand-written Chinese characters using on a simplified hidden Markov Random Field. MMIE provides improved performance improvement over MLE in this application.

Multi-font printed Mongolian document recognition system

NASA Astrophysics Data System (ADS)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

Development of an optical character recognition pipeline for handwritten form fields from an electronic health record.

PubMed

Rasmussen, Luke V; Peissig, Peggy L; McCarty, Catherine A; Starren, Justin

2012-06-01

Although the penetration of electronic health records is increasing rapidly, much of the historical medical record is only available in handwritten notes and forms, which require labor-intensive, human chart abstraction for some clinical research. The few previous studies on automated extraction of data from these handwritten notes have focused on monolithic, custom-developed recognition systems or third-party systems that require proprietary forms. We present an optical character recognition processing pipeline, which leverages the capabilities of existing third-party optical character recognition engines, and provides the flexibility offered by a modular custom-developed system. The system was configured and run on a selected set of form fields extracted from a corpus of handwritten ophthalmology forms. The processing pipeline allowed multiple configurations to be run, with the optimal configuration consisting of the Nuance and LEADTOOLS engines running in parallel with a positive predictive value of 94.6% and a sensitivity of 13.5%. While limitations exist, preliminary experience from this project yielded insights on the generalizability and applicability of integrating multiple, inexpensive general-purpose third-party optical character recognition engines in a modular pipeline.

Development of an optical character recognition pipeline for handwritten form fields from an electronic health record

PubMed Central

Peissig, Peggy L; McCarty, Catherine A; Starren, Justin

2011-01-01

Background Although the penetration of electronic health records is increasing rapidly, much of the historical medical record is only available in handwritten notes and forms, which require labor-intensive, human chart abstraction for some clinical research. The few previous studies on automated extraction of data from these handwritten notes have focused on monolithic, custom-developed recognition systems or third-party systems that require proprietary forms. Methods We present an optical character recognition processing pipeline, which leverages the capabilities of existing third-party optical character recognition engines, and provides the flexibility offered by a modular custom-developed system. The system was configured and run on a selected set of form fields extracted from a corpus of handwritten ophthalmology forms. Observations The processing pipeline allowed multiple configurations to be run, with the optimal configuration consisting of the Nuance and LEADTOOLS engines running in parallel with a positive predictive value of 94.6% and a sensitivity of 13.5%. Discussion While limitations exist, preliminary experience from this project yielded insights on the generalizability and applicability of integrating multiple, inexpensive general-purpose third-party optical character recognition engines in a modular pipeline. PMID:21890871

Public domain optical character recognition

NASA Astrophysics Data System (ADS)

Garris, Michael D.; Blue, James L.; Candela, Gerald T.; Dimmick, Darrin L.; Geist, Jon C.; Grother, Patrick J.; Janet, Stanley A.; Wilson, Charles L.

1995-03-01

A public domain document processing system has been developed by the National Institute of Standards and Technology (NIST). The system is a standard reference form-based handprint recognition system for evaluating optical character recognition (OCR), and it is intended to provide a baseline of performance on an open application. The system's source code, training data, performance assessment tools, and type of forms processed are all publicly available. The system recognizes the handprint entered on handwriting sample forms like the ones distributed with NIST Special Database 1. From these forms, the system reads hand-printed numeric fields, upper and lowercase alphabetic fields, and unconstrained text paragraphs comprised of words from a limited-size dictionary. The modular design of the system makes it useful for component evaluation and comparison, training and testing set validation, and multiple system voting schemes. The system contains a number of significant contributions to OCR technology, including an optimized probabilistic neural network (PNN) classifier that operates a factor of 20 times faster than traditional software implementations of the algorithm. The source code for the recognition system is written in C and is organized into 11 libraries. In all, there are approximately 19,000 lines of code supporting more than 550 subroutines. Source code is provided for form registration, form removal, field isolation, field segmentation, character normalization, feature extraction, character classification, and dictionary-based postprocessing. The recognition system has been successfully compiled and tested on a host of UNIX workstations. This paper gives an overview of the recognition system's software architecture, including descriptions of the various system components along with timing and accuracy statistics.

Hybrid neuro-fuzzy approach for automatic vehicle license plate recognition

NASA Astrophysics Data System (ADS)

Lee, Hsi-Chieh; Jong, Chung-Shi

1998-03-01

Most currently available vehicle identification systems use techniques such as R.F., microwave, or infrared to help identifying the vehicle. Transponders are usually installed in the vehicle in order to transmit the corresponding information to the sensory system. It is considered expensive to install a transponder in each vehicle and the malfunction of the transponder will result in the failure of the vehicle identification system. In this study, novel hybrid approach is proposed for automatic vehicle license plate recognition. A system prototype is built which can be used independently or cooperating with current vehicle identification system in identifying a vehicle. The prototype consists of four major modules including the module for license plate region identification, the module for character extraction from the license plate, the module for character recognition, and the module for the SimNet neuro-fuzzy system. To test the performance of the proposed system, three hundred and eighty vehicle image samples are taken by a digital camera. The license plate recognition success rate of the prototype is approximately 91% while the character recognition success rate of the prototype is approximately 97%.

Recognition of handprinted characters for automated cartography A progress report

NASA Technical Reports Server (NTRS)

Lybanon, M.; Brown, R. M.; Gronmeyer, L. K.

1980-01-01

A research program for developing handwritten character recognition techniques is reported. The generation of cartographic/hydrographic manuscripts is overviewed. The performance of hardware/software systems is discussed, along with future research problem areas and planned approaches.

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.

Application of the ANNA neural network chip to high-speed character recognition.

PubMed

Sackinger, E; Boser, B E; Bromley, J; Lecun, Y; Jackel, L D

1992-01-01

A neural network with 136000 connections for recognition of handwritten digits has been implemented using a mixed analog/digital neural network chip. The neural network chip is capable of processing 1000 characters/s. The recognition system has essentially the same rate (5%) as a simulation of the network with 32-b floating-point precision.

Principal Component 2-D Long Short-Term Memory for Font Recognition on Single Chinese Characters.

PubMed

Tao, Dapeng; Lin, Xu; Jin, Lianwen; Li, Xuelong

2016-03-01

Chinese character font recognition (CCFR) has received increasing attention as the intelligent applications based on optical character recognition becomes popular. However, traditional CCFR systems do not handle noisy data effectively. By analyzing in detail the basic strokes of Chinese characters, we propose that font recognition on a single Chinese character is a sequence classification problem, which can be effectively solved by recurrent neural networks. For robust CCFR, we integrate a principal component convolution layer with the 2-D long short-term memory (2DLSTM) and develop principal component 2DLSTM (PC-2DLSTM) algorithm. PC-2DLSTM considers two aspects: 1) the principal component layer convolution operation helps remove the noise and get a rational and complete font information and 2) simultaneously, 2DLSTM deals with the long-range contextual processing along scan directions that can contribute to capture the contrast between character trajectory and background. Experiments using the frequently used CCFR dataset suggest the effectiveness of PC-2DLSTM compared with other state-of-the-art font recognition methods.

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.

Intelligent form removal with character stroke preservation

NASA Astrophysics Data System (ADS)

Garris, Michael D.

1996-03-01

A new technique for intelligent form removal has been developed along with a new method for evaluating its impact on optical character recognition (OCR). All the dominant lines in the image are automatically detected using the Hough line transform and intelligently erased while simultaneously preserving overlapping character strokes by computing line width statistics and keying off of certain visual cues. This new method of form removal operates on loosely defined zones with no image deskewing. Any field in which the writer is provided a horizontal line to enter a response can be processed by this method. Several examples of processed fields are provided, including a comparison of results between the new method and a commercially available forms removal package. Even if this new form removal method did not improve character recognition accuracy, it is still a significant improvement to the technology because the requirement of a priori knowledge of the form's geometric details has been greatly reduced. This relaxes the recognition system's dependence on rigid form design, printing, and reproduction by automatically detecting and removing some of the physical structures (lines) on the form. Using the National Institute of Standards and Technology (NIST) public domain form-based handprint recognition system, the technique was tested on a large number of fields containing randomly ordered handprinted lowercase alphabets, as these letters (especially those with descenders) frequently touch and extend through the line along which they are written. Preserving character strokes improves overall lowercase recognition performance by 3%, which is a net improvement, but a single performance number like this doesn't communicate how the recognition process was really influenced. There is expected to be trade- offs with the introduction of any new technique into a complex recognition system. To understand both the improvements and the trade-offs, a new analysis was designed to compare the statistical distributions of individual confusion pairs between two systems. As OCR technology continues to improve, sophisticated analyses like this are necessary to reduce the errors remaining in complex recognition problems.

Guideline for Optical Character Recognition Forms.

ERIC Educational Resources Information Center

National Bureau of Standards (DOC), Washington, DC.

This publication provides materials relating to the design, preparation, acquisition, inspection, and application of Optical Character Recognition (OCR) forms in data entry systems. Since the materials are advisory and tutorial in nature, this publication has been issued as a guideline rather than as a standard in the Federal Information…

Document Form and Character Recognition using SVM

NASA Astrophysics Data System (ADS)

Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

2009-08-01

Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

Printed Arabic optical character segmentation

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Ayyesh, Muna; Qaroush, Aziz; Tumar, Iyad

2015-03-01

A considerable progress in recognition techniques for many non-Arabic characters has been achieved. In contrary, few efforts have been put on the research of Arabic characters. In any Optical Character Recognition (OCR) system the segmentation step is usually the essential stage in which an extensive portion of processing is devoted and a considerable share of recognition errors is attributed. In this research, a novel segmentation approach for machine Arabic printed text with diacritics is proposed. The proposed method reduces computation, errors, gives a clear description for the sub-word and has advantages over using the skeleton approach in which the data and information of the character can be lost. Both of initial evaluation and testing of the proposed method have been developed using MATLAB and shows 98.7% promising results.

Optical character recognition of camera-captured images based on phase features

NASA Astrophysics Data System (ADS)

Diaz-Escobar, Julia; Kober, Vitaly

2015-09-01

Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.

AN OPTICAL CHARACTER RECOGNITION RESEARCH AND DEMONSTRATION PROJECT.

ERIC Educational Resources Information Center

1968

RESEARCH AND DEVELOPMENT OF PROTOTYPE LIBRARY SYSTEMS WHICH UTILIZE OPTICAL CHARACTER RECOGNITION INPUT HAS CENTERED AROUND OPTICAL PAGE READERS AND DOCUMENT READERS. THE STATE-OF-THE-ART OF BOTH THESE OPTICAL SCANNERS IS SUCH THAT BOTH ARE ACCEPTABLE FOR LIBRARY INPUT PREPARATION. A DEMONSTRATION PROJECT UTILIZING THE TWO TYPES OF READERS, SINCE…

Recognizing characters of ancient manuscripts

NASA Astrophysics Data System (ADS)

Diem, Markus; Sablatnig, Robert

2010-02-01

Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.

Holistic neural coding of Chinese character forms in bilateral ventral visual system.

PubMed

Mo, Ce; Yu, Mengxia; Seger, Carol; Mo, Lei

2015-02-01

How are Chinese characters recognized and represented in the brain of skilled readers? Functional MRI fast adaptation technique was used to address this question. We found that neural adaptation effects were limited to identical characters in bilateral ventral visual system while no activation reduction was observed for partially overlapping characters regardless of the spatial location of the shared sub-character components, suggesting highly selective neuronal tuning to whole characters. The consistent neural profile across the entire ventral visual cortex indicates that Chinese characters are represented as mutually distinctive wholes rather than combinations of sub-character components, which presents a salient contrast to the left-lateralized, simple-to-complex neural representations of alphabetic words. Our findings thus revealed the cultural modulation effect on both local neuronal activity patterns and functional anatomical regions associated with written symbol recognition. Moreover, the cross-language discrepancy in written symbol recognition mechanism might stem from the language-specific early-stage learning experience. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Good initialization model with constrained body structure for scene text recognition

NASA Astrophysics Data System (ADS)

Zhu, Anna; Wang, Guoyou; Dong, Yangbo

2016-09-01

Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

Cost-Effective CNC Part Program Verification Development for Laboratory Instruction.

ERIC Educational Resources Information Center

Chen, Joseph C.; Chang, Ted C.

2000-01-01

Describes a computer numerical control program verification system that checks a part program before its execution. The system includes character recognition, word recognition, a fuzzy-nets system, and a tool path viewer. (SK)

A New Experiment on Bengali Character Recognition

NASA Astrophysics Data System (ADS)

Barman, Sumana; Bhattacharyya, Debnath; Jeon, Seung-Whan; Kim, Tai-Hoon; Kim, Haeng-Kon

This paper presents a method to use View based approach in Bangla Optical Character Recognition (OCR) system providing reduced data set to the ANN classification engine rather than the traditional OCR methods. It describes how Bangla characters are processed, trained and then recognized with the use of a Backpropagation Artificial neural network. This is the first published account of using a segmentation-free optical character recognition system for Bangla using a view based approach. The methodology presented here assumes that the OCR pre-processor has presented the input images to the classification engine described here. The size and the font face used to render the characters are also significant in both training and classification. The images are first converted into greyscale and then to binary images; these images are then scaled to a fit a pre-determined area with a fixed but significant number of pixels. The feature vectors are then formed extracting the characteristics points, which in this case is simply a series of 0s and 1s of fixed length. Finally, an artificial neural network is chosen for the training and classification process.

Scene text recognition in mobile applications by character descriptor and structure configuration.

PubMed

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

Performance evaluation of MLP and RBF feed forward neural network for the recognition of off-line handwritten characters

NASA Astrophysics Data System (ADS)

Rishi, Rahul; Choudhary, Amit; Singh, Ravinder; Dhaka, Vijaypal Singh; Ahlawat, Savita; Rao, Mukta

2010-02-01

In this paper we propose a system for classification problem of handwritten text. The system is composed of preprocessing module, supervised learning module and recognition module on a very broad level. The preprocessing module digitizes the documents and extracts features (tangent values) for each character. The radial basis function network is used in the learning and recognition modules. The objective is to analyze and improve the performance of Multi Layer Perceptron (MLP) using RBF transfer functions over Logarithmic Sigmoid Function. The results of 35 experiments indicate that the Feed Forward MLP performs accurately and exhaustively with RBF. With the change in weight update mechanism and feature-drawn preprocessing module, the proposed system is competent with good recognition show.

The Compensatory Effectiveness of Optical Character Recognition/Speech Synthesis on Reading Comprehension of Postsecondary Students with Learning Disabilities.

ERIC Educational Resources Information Center

Higgins, Eleanor L.; Raskind, Marshall H.

1997-01-01

Thirty-seven college students with learning disabilities were given a reading comprehension task under the following conditions: (1) using an optical character recognition/speech synthesis system; (2) having the text read aloud by a human reader; or (3) reading silently without assistance. Findings indicated that the greater the disability, the…

Nonlinear filtering for character recognition in low quality document images

NASA Astrophysics Data System (ADS)

Diaz-Escobar, Julia; Kober, Vitaly

2014-09-01

Optical character recognition in scanned printed documents is a well-studied task, where the captured conditions like sheet position, illumination, contrast and resolution are controlled. Nowadays, it is more practical to use mobile devices for document capture than a scanner. So as a consequence, the quality of document images is often poor owing to presence of geometric distortions, nonhomogeneous illumination, low resolution, etc. In this work we propose to use multiple adaptive nonlinear composite filters for detection and classification of characters. Computer simulation results obtained with the proposed system are presented and discussed.

Chinese character recognition based on Gabor feature extraction and CNN

NASA Astrophysics Data System (ADS)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Cognitive Processing Hardware Elements

DTIC Science & Technology

2005-01-31

characters. Results will be presented below. 1 4. Recognition of human faces. There are many other possible applications such as facial recognition and...For the experiments in facial recognition , we have used a 3-layer autoassociative neural network having the following specifications: "* The input...using the facial recognition system described in the section above as an example. This system uses an autoassociative neural network containing over 10

Address entry while driving: speech recognition versus a touch-screen keyboard.

PubMed

Tsimhoni, Omer; Smith, Daniel; Green, Paul

2004-01-01

A driving simulator experiment was conducted to determine the effects of entering addresses into a navigation system during driving. Participants drove on roads of varying visual demand while entering addresses. Three address entry methods were explored: word-based speech recognition, character-based speech recognition, and typing on a touch-screen keyboard. For each method, vehicle control and task measures, glance timing, and subjective ratings were examined. During driving, word-based speech recognition yielded the shortest total task time (15.3 s), followed by character-based speech recognition (41.0 s) and touch-screen keyboard (86.0 s). The standard deviation of lateral position when performing keyboard entry (0.21 m) was 60% higher than that for all other address entry methods (0.13 m). Degradation of vehicle control associated with address entry using a touch screen suggests that the use of speech recognition is favorable. Speech recognition systems with visual feedback, however, even with excellent accuracy, are not without performance consequences. Applications of this research include the design of in-vehicle navigation systems as well as other systems requiring significant driver input, such as E-mail, the Internet, and text messaging.

A new pre-classification method based on associative matching method

NASA Astrophysics Data System (ADS)

Katsuyama, Yutaka; Minagawa, Akihiro; Hotta, Yoshinobu; Omachi, Shinichiro; Kato, Nei

2010-01-01

Reducing the time complexity of character matching is critical to the development of efficient Japanese Optical Character Recognition (OCR) systems. To shorten processing time, recognition is usually split into separate preclassification and recognition stages. For high overall recognition performance, the pre-classification stage must both have very high classification accuracy and return only a small number of putative character categories for further processing. Furthermore, for any practical system, the speed of the pre-classification stage is also critical. The associative matching (AM) method has often been used for fast pre-classification, because its use of a hash table and reliance solely on logical bit operations to select categories makes it highly efficient. However, redundant certain level of redundancy exists in the hash table because it is constructed using only the minimum and maximum values of the data on each axis and therefore does not take account of the distribution of the data. We propose a modified associative matching method that satisfies the performance criteria described above but in a fraction of the time by modifying the hash table to reflect the underlying distribution of training characters. Furthermore, we show that our approach outperforms pre-classification by clustering, ANN and conventional AM in terms of classification accuracy, discriminative power and speed. Compared to conventional associative matching, the proposed approach results in a 47% reduction in total processing time across an evaluation test set comprising 116,528 Japanese character images.

Rapid Naming Speed and Chinese Character Recognition

ERIC Educational Resources Information Center

Liao, Chen-Huei; Georgiou, George K.; Parrila, Rauno

2008-01-01

We examined the relationship between rapid naming speed (RAN) and Chinese character recognition accuracy and fluency. Sixty-three grade 2 and 54 grade 4 Taiwanese children were administered four RAN tasks (colors, digits, Zhu-Yin-Fu-Hao, characters), and two character recognition tasks. RAN tasks accounted for more reading variance in grade 4 than…

Practical vision based degraded text recognition system

NASA Astrophysics Data System (ADS)

Mohammad, Khader; Agaian, Sos; Saleh, Hani

2011-02-01

Rapid growth and progress in the medical, industrial, security and technology fields means more and more consideration for the use of camera based optical character recognition (OCR) Applying OCR to scanned documents is quite mature, and there are many commercial and research products available on this topic. These products achieve acceptable recognition accuracy and reasonable processing times especially with trained software, and constrained text characteristics. Even though the application space for OCR is huge, it is quite challenging to design a single system that is capable of performing automatic OCR for text embedded in an image irrespective of the application. Challenges for OCR systems include; images are taken under natural real world conditions, Surface curvature, text orientation, font, size, lighting conditions, and noise. These and many other conditions make it extremely difficult to achieve reasonable character recognition. Performance for conventional OCR systems drops dramatically as the degradation level of the text image quality increases. In this paper, a new recognition method is proposed to recognize solid or dotted line degraded characters. The degraded text string is localized and segmented using a new algorithm. The new method was implemented and tested using a development framework system that is capable of performing OCR on camera captured images. The framework allows parameter tuning of the image-processing algorithm based on a training set of camera-captured text images. Novel methods were used for enhancement, text localization and the segmentation algorithm which enables building a custom system that is capable of performing automatic OCR which can be used for different applications. The developed framework system includes: new image enhancement, filtering, and segmentation techniques which enabled higher recognition accuracies, faster processing time, and lower energy consumption, compared with the best state of the art published techniques. The system successfully produced impressive OCR accuracies (90% -to- 93%) using customized systems generated by our development framework in two industrial OCR applications: water bottle label text recognition and concrete slab plate text recognition. The system was also trained for the Arabic language alphabet, and demonstrated extremely high recognition accuracy (99%) for Arabic license name plate text recognition with processing times of 10 seconds. The accuracy and run times of the system were compared to conventional and many states of art methods, the proposed system shows excellent results.

Kanji Recognition by Second Language Learners: Exploring Effects of First Language Writing Systems and Second Language Exposure

ERIC Educational Resources Information Center

Matsumoto, Kazumi

2013-01-01

This study investigated whether learners of Japanese with different first language (L1) writing systems use different recognition strategies and whether second language (L2) exposure affects L2 kanji recognition. The study used a computerized lexical judgment task with 3 types of kanji characters to investigate these questions: (a)…

Fast title extraction method for business documents

NASA Astrophysics Data System (ADS)

Katsuyama, Yutaka; Naoi, Satoshi

1997-04-01

Conventional electronic document filing systems are inconvenient because the user must specify the keywords in each document for later searches. To solve this problem, automatic keyword extraction methods using natural language processing and character recognition have been developed. However, these methods are slow, especially for japanese documents. To develop a practical electronic document filing system, we focused on the extraction of keyword areas from a document by image processing. Our fast title extraction method can automatically extract titles as keywords from business documents. All character strings are evaluated for similarity by rating points associated with title similarity. We classified these points as four items: character sitting size, position of character strings, relative position among character strings, and string attribution. Finally, the character string that has the highest rating is selected as the title area. The character recognition process is carried out on the selected area. It is fast because this process must recognize a small number of patterns in the restricted area only, and not throughout the entire document. The mean performance of this method is an accuracy of about 91 percent and a 1.8 sec. processing time for an examination of 100 Japanese business documents.

A distinguishing method of printed and handwritten legal amount on Chinese bank check

NASA Astrophysics Data System (ADS)

Zhu, Ningbo; Lou, Zhen; Yang, Jingyu

2003-09-01

While carrying out Optical Chinese Character Recognition, distinguishing the font between printed and handwritten characters at the early phase is necessary, because there is so much difference between the methods on recognizing these two types of characters. In this paper, we proposed a good method on how to banish seals and its relative standards that can judge whether they should be banished. Meanwhile, an approach on clearing up scattered noise shivers after image segmentation is presented. Four sets of classifying features that show discrimination between printed and handwritten characters are well adopted. The proposed approach was applied to an automatic check processing system and tested on about 9031 checks. The recognition rate is more than 99.5%.

Comparative implementation of Handwritten and Machine written Gurmukhi text utilizing appropriate parameters

NASA Astrophysics Data System (ADS)

Kaur, Jaswinder; Jagdev, Gagandeep, Dr.

2018-01-01

Optical character recognition is concerned with the recognition of optically processed characters. The recognition is done offline after the writing or printing has been completed, unlike online recognition where the computer has to recognize the characters instantly as they are drawn. The performance of character recognition depends upon the quality of scanned documents. The preprocessing steps are used for removing low-frequency background noise and normalizing the intensity of individual scanned documents. Several filters are used for reducing certain image details and enabling an easier or faster evaluation. The primary aim of the research work is to recognize handwritten and machine written characters and differentiate them. The language opted for the research work is Punjabi Gurmukhi and tool utilized is Matlab.

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.

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.

Children's Recognition of Cartoon Voices.

ERIC Educational Resources Information Center

Spence, Melanie J.; Rollins, Pamela R.; Jerger, Susan

2002-01-01

A study examined developmental changes in talker recognition skills by assessing 72 children's (ages 3-5) recognition of 20 cartoon characters' voices. Four- and 5-year-old children recognized more of the voices than did 3-year-olds. All children were more accurate at recognizing more familiar characters than less familiar characters. (Contains…

Low-Budget, Cost-Effective OCR: Optical Character Recognition for MS-DOS Micros.

ERIC Educational Resources Information Center

Perez, Ernest

1990-01-01

Discusses optical character recognition (OCR) for use with MS-DOS microcomputers. Cost effectiveness is considered, three types of software approaches to character recognition are explained, hardware and operation requirements are described, possible library applications are discussed, future OCR developments are suggested, and a list of OCR…

Online recognition of Chinese characters: the state-of-the-art.

PubMed

Liu, Cheng-Lin; Jaeger, Stefan; Nakagawa, Masaki

2004-02-01

Online handwriting recognition is gaining renewed interest owing to the increase of pen computing applications and new pen input devices. The recognition of Chinese characters is different from western handwriting recognition and poses a special challenge. To provide an overview of the technical status and inspire future research, this paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s. Compared to the research in the 1980s, the research efforts in the 1990s aimed to further relax the constraints of handwriting, namely, the adherence to standard stroke orders and stroke numbers and the restriction of recognition to isolated characters only. The target of recognition has shifted from regular script to fluent script in order to better meet the requirements of practical applications. The research works are reviewed in terms of pattern representation, character classification, learning/adaptation, and contextual processing. We compare important results and discuss possible directions of future research.

Development of Portable Automatic Number Plate Recognition System on Android Mobile Phone

NASA Astrophysics Data System (ADS)

Mutholib, Abdul; Gunawan, Teddy S.; Chebil, Jalel; Kartiwi, Mira

2013-12-01

The Automatic Number Plate Recognition (ANPR) System has performed as the main role in various access control and security, such as: tracking of stolen vehicles, traffic violations (speed trap) and parking management system. In this paper, the portable ANPR implemented on android mobile phone is presented. The main challenges in mobile application are including higher coding efficiency, reduced computational complexity, and improved flexibility. Significance efforts are being explored to find suitable and adaptive algorithm for implementation of ANPR on mobile phone. ANPR system for mobile phone need to be optimize due to its limited CPU and memory resources, its ability for geo-tagging image captured using GPS coordinates and its ability to access online database to store the vehicle's information. In this paper, the design of portable ANPR on android mobile phone will be described as follows. First, the graphical user interface (GUI) for capturing image using built-in camera was developed to acquire vehicle plate number in Malaysia. Second, the preprocessing of raw image was done using contrast enhancement. Next, character segmentation using fixed pitch and an optical character recognition (OCR) using neural network were utilized to extract texts and numbers. Both character segmentation and OCR were using Tesseract library from Google Inc. The proposed portable ANPR algorithm was implemented and simulated using Android SDK on a computer. Based on the experimental results, the proposed system can effectively recognize the license plate number at 90.86%. The required processing time to recognize a license plate is only 2 seconds on average. The result is consider good in comparison with the results obtained from previous system that was processed in a desktop PC with the range of result from 91.59% to 98% recognition rate and 0.284 second to 1.5 seconds recognition time.

Recognition of Telugu characters using neural networks.

PubMed

Sukhaswami, M B; Seetharamulu, P; Pujari, A K

1995-09-01

The aim of the present work is to recognize printed and handwritten Telugu characters using artificial neural networks (ANNs). Earlier work on recognition of Telugu characters has been done using conventional pattern recognition techniques. We make an initial attempt here of using neural networks for recognition with the aim of improving upon earlier methods which do not perform effectively in the presence of noise and distortion in the characters. The Hopfield model of neural network working as an associative memory is chosen for recognition purposes initially. Due to limitation in the capacity of the Hopfield neural network, we propose a new scheme named here as the Multiple Neural Network Associative Memory (MNNAM). The limitation in storage capacity has been overcome by combining multiple neural networks which work in parallel. It is also demonstrated that the Hopfield network is suitable for recognizing noisy printed characters as well as handwritten characters written by different "hands" in a variety of styles. Detailed experiments have been carried out using several learning strategies and results are reported. It is shown here that satisfactory recognition is possible using the proposed strategy. A detailed preprocessing scheme of the Telugu characters from digitized documents is also described.

A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.

PubMed

Biondich, Paul G; Overhage, J Marc; Dexter, Paul R; Downs, Stephen M; Lemmon, Larry; McDonald, Clement J

2002-01-01

Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data.

Visual Similarity of Words Alone Can Modulate Hemispheric Lateralization in Visual Word Recognition: Evidence from Modeling Chinese Character Recognition

ERIC Educational Resources Information Center

Hsiao, Janet H.; Cheung, Kit

2016-01-01

In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right (SP characters); the minority, opposite arrangement also exists (PS characters). Recent studies showed that SP character processing is more left hemisphere (LH) lateralized than PS character processing.…

Optical character recognition: an illustrated guide to the frontier

NASA Astrophysics Data System (ADS)

Nagy, George; Nartker, Thomas A.; Rice, Stephen V.

1999-12-01

We offer a perspective on the performance of current OCR systems by illustrating and explaining actual OCR errors made by three commercial devices. After discussing briefly the character recognition abilities of humans and computers, we present illustrated examples of recognition errors. The top level of our taxonomy of the causes of errors consists of Imaging Defects, Similar Symbols, Punctuation, and Typography. The analysis of a series of 'snippets' from this perspective provides insight into the strengths and weaknesses of current systems, and perhaps a road map to future progress. The examples were drawn from the large-scale tests conducted by the authors at the Information Science Research Institute of the University of Nevada, Las Vegas. By way of conclusion, we point to possible approaches for improving the accuracy of today's systems. The talk is based on our eponymous monograph, recently published in The Kluwer International Series in Engineering and Computer Science, Kluwer Academic Publishers, 1999.

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.

Common constraints limit Korean and English character recognition in peripheral vision.

PubMed

He, Yingchen; Kwon, MiYoung; Legge, Gordon E

2018-01-01

The visual span refers to the number of adjacent characters that can be recognized in a single glance. It is viewed as a sensory bottleneck in reading for both normal and clinical populations. In peripheral vision, the visual span for English characters can be enlarged after training with a letter-recognition task. Here, we examined the transfer of training from Korean to English characters for a group of bilingual Korean native speakers. In the pre- and posttests, we measured visual spans for Korean characters and English letters. Training (1.5 hours × 4 days) consisted of repetitive visual-span measurements for Korean trigrams (strings of three characters). Our training enlarged the visual spans for Korean single characters and trigrams, and the benefit transferred to untrained English symbols. The improvement was largely due to a reduction of within-character and between-character crowding in Korean recognition, as well as between-letter crowding in English recognition. We also found a negative correlation between the size of the visual span and the average pattern complexity of the symbol set. Together, our results showed that the visual span is limited by common sensory (crowding) and physical (pattern complexity) factors regardless of the language script, providing evidence that the visual span reflects a universal bottleneck for text recognition.

Common constraints limit Korean and English character recognition in peripheral vision

PubMed Central

He, Yingchen; Kwon, MiYoung; Legge, Gordon E.

2018-01-01

The visual span refers to the number of adjacent characters that can be recognized in a single glance. It is viewed as a sensory bottleneck in reading for both normal and clinical populations. In peripheral vision, the visual span for English characters can be enlarged after training with a letter-recognition task. Here, we examined the transfer of training from Korean to English characters for a group of bilingual Korean native speakers. In the pre- and posttests, we measured visual spans for Korean characters and English letters. Training (1.5 hours × 4 days) consisted of repetitive visual-span measurements for Korean trigrams (strings of three characters). Our training enlarged the visual spans for Korean single characters and trigrams, and the benefit transferred to untrained English symbols. The improvement was largely due to a reduction of within-character and between-character crowding in Korean recognition, as well as between-letter crowding in English recognition. We also found a negative correlation between the size of the visual span and the average pattern complexity of the symbol set. Together, our results showed that the visual span is limited by common sensory (crowding) and physical (pattern complexity) factors regardless of the language script, providing evidence that the visual span reflects a universal bottleneck for text recognition. PMID:29327041

Character-level neural network for biomedical named entity recognition.

PubMed

Gridach, Mourad

2017-06-01

Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

Character Recognition Using Genetically Trained Neural Networks

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

Diniz, C.; Stantz, K.M.; Trahan, M.W.

1998-10-01

Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfidmore » recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the amount of noise significantly degrades character recognition efficiency, some of which can be overcome by adding noise during training and optimizing the form of the network's activation fimction.« less

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.

Optical character recognition of handwritten Arabic using hidden Markov models

NASA Astrophysics Data System (ADS)

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

2011-04-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

Optical character recognition of handwritten Arabic using hidden Markov models

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

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.

2011-01-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language ismore » initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.« less

A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.

PubMed Central

Biondich, Paul G.; Overhage, J. Marc; Dexter, Paul R.; Downs, Stephen M.; Lemmon, Larry; McDonald, Clement J.

2002-01-01

Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data. PMID:12463786

A Development of a System Enables Character Input and PC Operation via Voice for a Physically Disabled Person with a Speech Impediment

NASA Astrophysics Data System (ADS)

Tanioka, Toshimasa; Egashira, Hiroyuki; Takata, Mayumi; Okazaki, Yasuhisa; Watanabe, Kenzi; Kondo, Hiroki

We have designed and implemented a PC operation support system for a physically disabled person with a speech impediment via voice. Voice operation is an effective method for a physically disabled person with involuntary movement of the limbs and the head. We have applied a commercial speech recognition engine to develop our system for practical purposes. Adoption of a commercial engine reduces development cost and will contribute to make our system useful to another speech impediment people. We have customized commercial speech recognition engine so that it can recognize the utterance of a person with a speech impediment. We have restricted the words that the recognition engine recognizes and separated a target words from similar words in pronunciation to avoid misrecognition. Huge number of words registered in commercial speech recognition engines cause frequent misrecognition for speech impediments' utterance, because their utterance is not clear and unstable. We have solved this problem by narrowing the choice of input down in a small number and also by registering their ambiguous pronunciations in addition to the original ones. To realize all character inputs and all PC operation with a small number of words, we have designed multiple input modes with categorized dictionaries and have introduced two-step input in each mode except numeral input to enable correct operation with small number of words. The system we have developed is in practical level. The first author of this paper is physically disabled with a speech impediment. He has been able not only character input into PC but also to operate Windows system smoothly by using this system. He uses this system in his daily life. This paper is written by him with this system. At present, the speech recognition is customized to him. It is, however, possible to customize for other users by changing words and registering new pronunciation according to each user's utterance.

Assistive Technology and Adults with Learning Disabilities: A Blueprint for Exploration and Advancement.

ERIC Educational Resources Information Center

Raskind, Marshall

1993-01-01

This article describes assistive technologies for persons with learning disabilities, including word processing, spell checking, proofreading programs, outlining/"brainstorming" programs, abbreviation expanders, speech recognition, speech synthesis/screen review, optical character recognition systems, personal data managers, free-form databases,…

Character recognition using a neural network model with fuzzy representation

NASA Technical Reports Server (NTRS)

Tavakoli, Nassrin; Seniw, David

1992-01-01

The degree to which digital images are recognized correctly by computerized algorithms is highly dependent upon the representation and the classification processes. Fuzzy techniques play an important role in both processes. In this paper, the role of fuzzy representation and classification on the recognition of digital characters is investigated. An experimental Neural Network model with application to character recognition was developed. Through a set of experiments, the effect of fuzzy representation on the recognition accuracy of this model is presented.

Sunspot drawings handwritten character recognition method based on deep learning

NASA Astrophysics Data System (ADS)

Zheng, Sheng; Zeng, Xiangyun; Lin, Ganghua; Zhao, Cui; Feng, Yongli; Tao, Jinping; Zhu, Daoyuan; Xiong, Li

2016-05-01

High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.

Robust recognition of degraded machine-printed characters using complementary similarity measure and error-correction learning

NASA Astrophysics Data System (ADS)

Hagita, Norihiro; Sawaki, Minako

1995-03-01

Most conventional methods in character recognition extract geometrical features such as stroke direction, connectivity of strokes, etc., and compare them with reference patterns in a stored dictionary. Unfortunately, geometrical features are easily degraded by blurs, stains and the graphical background designs used in Japanese newspaper headlines. This noise must be removed before recognition commences, but no preprocessing method is completely accurate. This paper proposes a method for recognizing degraded characters and characters printed on graphical background designs. This method is based on the binary image feature method and uses binary images as features. A new similarity measure, called the complementary similarity measure, is used as a discriminant function. It compares the similarity and dissimilarity of binary patterns with reference dictionary patterns. Experiments are conducted using the standard character database ETL-2 which consists of machine-printed Kanji, Hiragana, Katakana, alphanumeric, an special characters. The results show that this method is much more robust against noise than the conventional geometrical feature method. It also achieves high recognition rates of over 92% for characters with textured foregrounds, over 98% for characters with textured backgrounds, over 98% for outline fonts, and over 99% for reverse contrast characters.

Development of OCR system for portable passport and visa reader

NASA Astrophysics Data System (ADS)

Visilter, Yury V.; Zheltov, Sergey Y.; Lukin, Anton A.

1999-01-01

The modern passport and visa documents include special machine-readable zones satisfied the ICAO standards. This allows to develop the special passport and visa automatic readers. However, there are some special problems in such OCR systems: low resolution of character images captured by CCD-camera (down to 150 dpi), essential shifts and slopes (up to 10 degrees), rich paper texture under the character symbols, non-homogeneous illumination. This paper presents the structure and some special aspects of OCR system for portable passport and visa reader. In our approach the binarization procedure is performed after the segmentation step, and it is applied to the each character site separately. Character recognition procedure uses the structural information of machine-readable zone. Special algorithms are developed for machine-readable zone extraction and character segmentation.

Computerized literature reference system: use of an optical scanner and optical character recognition software.

PubMed

Lossef, S V; Schwartz, L H

1990-09-01

A computerized reference system for radiology journal articles was developed by using an IBM-compatible personal computer with a hand-held optical scanner and optical character recognition software. This allows direct entry of scanned text from printed material into word processing or data-base files. Additionally, line diagrams and photographs of radiographs can be incorporated into these files. A text search and retrieval software program enables rapid searching for keywords in scanned documents. The hand scanner and software programs are commercially available, relatively inexpensive, and easily used. This permits construction of a personalized radiology literature file of readily accessible text and images requiring minimal typing or keystroke entry.

Writing Strengthens Orthography and Alphabetic-Coding Strengthens Phonology in Learning to Read Chinese

ERIC Educational Resources Information Center

Guan, Connie Qun; Liu, Ying; Chan, Derek Ho Leung; Ye, Feifei; Perfetti, Charles A.

2011-01-01

Learning to write words may strengthen orthographic representations and thus support word-specific recognition processes. This hypothesis applies especially to Chinese because its writing system encourages character-specific recognition that depends on accurate representation of orthographic form. We report 2 studies that test this hypothesis in…

The Effects of Noisy Data on Text Retrieval.

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1994-01-01

Discusses the use of optical character recognition (OCR) for inputting documents in an information retrieval system and describes a study that used an OCR-generated database and its corresponding corrected version to examine query evaluation in the presence of noisy data. Scanning technology, recognition technology, and retrieval technology are…

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

2001-03-01

This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

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.

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.

Writing affects the brain network of reading in Chinese: a functional magnetic resonance imaging study.

PubMed

Cao, Fan; Vu, Marianne; Chan, Derek Ho Lung; Lawrence, Jason M; Harris, Lindsay N; Guan, Qun; Xu, Yi; Perfetti, Charles A

2013-07-01

We examined the hypothesis that learning to write Chinese characters influences the brain's reading network for characters. Students from a college Chinese class learned 30 characters in a character-writing condition and 30 characters in a pinyin-writing condition. After learning, functional magnetic resonance imaging collected during passive viewing showed different networks for reading Chinese characters and English words, suggesting accommodation to the demands of the new writing system through short-term learning. Beyond these expected differences, we found specific effects of character writing in greater activation (relative to pinyin writing) in bilateral superior parietal lobules and bilateral lingual gyri in both a lexical decision and an implicit writing task. These findings suggest that character writing establishes a higher quality representation of the visual-spatial structure of the character and its orthography. We found a greater involvement of bilateral sensori-motor cortex (SMC) for character-writing trained characters than pinyin-writing trained characters in the lexical decision task, suggesting that learning by doing invokes greater interaction with sensori-motor information during character recognition. Furthermore, we found a correlation of recognition accuracy with activation in right superior parietal lobule, right lingual gyrus, and left SMC, suggesting that these areas support the facilitative effect character writing has on reading. Finally, consistent with previous behavioral studies, we found character-writing training facilitates connections with semantics by producing greater activation in bilateral middle temporal gyri, whereas pinyin-writing training facilitates connections with phonology by producing greater activation in right inferior frontal gyrus. Copyright © 2012 Wiley Periodicals, Inc.

Early Reading Development in Chinese-Speaking Children with Hearing Loss

ERIC Educational Resources Information Center

Chan, Yi-Chih; Yang, You-Jhen

2018-01-01

This study aims to explore early reading comprehension in Chinese-speaking children with hearing loss (HL) by examining character recognition and linguistic comprehension. Twenty-five children with HL received three measures relevant to character reading: phonological awareness (PA), morphological awareness (MA), and character recognition; two…

Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

NASA Astrophysics Data System (ADS)

Popko, E. A.; Weinstein, I. A.

2016-08-01

Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.

Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial.

PubMed

Vogel, Markus; Kaisers, Wolfgang; Wassmuth, Ralf; Mayatepek, Ertan

2015-11-03

Clinical documentation has undergone a change due to the usage of electronic health records. The core element is to capture clinical findings and document therapy electronically. Health care personnel spend a significant portion of their time on the computer. Alternatives to self-typing, such as speech recognition, are currently believed to increase documentation efficiency and quality, as well as satisfaction of health professionals while accomplishing clinical documentation, but few studies in this area have been published to date. This study describes the effects of using a Web-based medical speech recognition system for clinical documentation in a university hospital on (1) documentation speed, (2) document length, and (3) physician satisfaction. Reports of 28 physicians were randomized to be created with (intervention) or without (control) the assistance of a Web-based system of medical automatic speech recognition (ASR) in the German language. The documentation was entered into a browser's text area and the time to complete the documentation including all necessary corrections, correction effort, number of characters, and mood of participant were stored in a database. The underlying time comprised text entering, text correction, and finalization of the documentation event. Participants self-assessed their moods on a scale of 1-3 (1=good, 2=moderate, 3=bad). Statistical analysis was done using permutation tests. The number of clinical reports eligible for further analysis stood at 1455. Out of 1455 reports, 718 (49.35%) were assisted by ASR and 737 (50.65%) were not assisted by ASR. Average documentation speed without ASR was 173 (SD 101) characters per minute, while it was 217 (SD 120) characters per minute using ASR. The overall increase in documentation speed through Web-based ASR assistance was 26% (P=.04). Participants documented an average of 356 (SD 388) characters per report when not assisted by ASR and 649 (SD 561) characters per report when assisted by ASR. Participants' average mood rating was 1.3 (SD 0.6) using ASR assistance compared to 1.6 (SD 0.7) without ASR assistance (P<.001). We conclude that medical documentation with the assistance of Web-based speech recognition leads to an increase in documentation speed, document length, and participant mood when compared to self-typing. Speech recognition is a meaningful and effective tool for the clinical documentation process.

Speech Recognition Technology for Disabilities Education

ERIC Educational Resources Information Center

Tang, K. Wendy; Kamoua, Ridha; Sutan, Victor; Farooq, Omer; Eng, Gilbert; Chu, Wei Chern; Hou, Guofeng

2005-01-01

Speech recognition is an alternative to traditional methods of interacting with a computer, such as textual input through a keyboard. An effective system can replace or reduce the reliability on standard keyboard and mouse input. This can especially assist dyslexic students who have problems with character or word use and manipulation in a textual…

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

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.

Quantum-Limited Image Recognition

DTIC Science & Technology

1989-12-01

J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 53. D. Barnea and H. Silverman...for Chapter 6 1. J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 2. D. Bamea and H

Transfer of Perceptual Expertise: The Case of Simplified and Traditional Chinese Character Recognition

ERIC Educational Resources Information Center

Liu, Tianyin; Chuk, Tin Yim; Yeh, Su-Ling; Hsiao, Janet H.

2016-01-01

Expertise in Chinese character recognition is marked by reduced holistic processing (HP), which depends mainly on writing rather than reading experience. Here we show that, while simplified and traditional Chinese readers demonstrated a similar level of HP when processing characters shared between the simplified and traditional scripts, simplified…

Construction of language models for an handwritten mail reading system

NASA Astrophysics Data System (ADS)

Morillot, Olivier; Likforman-Sulem, Laurence; Grosicki, Emmanuèle

2012-01-01

This paper presents a system for the recognition of unconstrained handwritten mails. The main part of this system is an HMM recognizer which uses trigraphs to model contextual information. This recognition system does not require any segmentation into words or characters and directly works at line level. To take into account linguistic information and enhance performance, a language model is introduced. This language model is based on bigrams and built from training document transcriptions only. Different experiments with various vocabulary sizes and language models have been conducted. Word Error Rate and Perplexity values are compared to show the interest of specific language models, fit to handwritten mail recognition task.

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Iterative cross section sequence graph for handwritten character segmentation.

PubMed

Dawoud, Amer

2007-08-01

The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.

Interspecific aggression and character displacement of competitor recognition in Hetaerina damselflies.

PubMed

Anderson, Christopher N; Grether, Gregory F

2010-02-22

In zones of sympatry between closely related species, species recognition errors in a competitive context can cause character displacement in agonistic signals and competitor recognition functions, just as species recognition errors in a mating context can cause character displacement in mating signals and mate recognition. These two processes are difficult to distinguish because the same traits can serve as both agonistic and mating signals. One solution is to test for sympatric shifts in recognition functions. We studied competitor recognition in Hetaerina damselflies by challenging territory holders with live tethered conspecific and heterospecific intruders. Heterospecific intruders elicited less aggression than conspecific intruders in species pairs with dissimilar wing coloration (H. occisa/H. titia, H. americana/H. titia) but not in species pairs with similar wing coloration (H. occisa/H. cruentata, H. americana/H. cruentata). Natural variation in the area of black wing pigmentation on H. titia intruders correlated negatively with heterospecific aggression. To directly examine the role of wing coloration, we blackened the wings of H. occisa or H. americana intruders and measured responses of conspecific territory holders. This treatment reduced territorial aggression at multiple sites where H. titia is present, but not at allopatric sites. These results provide strong evidence for agonistic character displacement.

Detailed Phonetic Labeling of Multi-language Database for Spoken Language Processing Applications

DTIC Science & Technology

2015-03-01

which contains about 60 interfering speakers as well as background music in a bar. The top panel is again clean training /noisy testing settings, and...recognition system for Mandarin was developed and tested. Character recognition rates as high as 88% were obtained, using an approximately 40 training ...Tool_ComputeFeat.m) .............................................................................................................. 50 6.3. Training

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.

Semi-automated contour recognition using DICOMautomaton

NASA Astrophysics Data System (ADS)

Clark, H.; Wu, J.; Moiseenko, V.; Lee, R.; Gill, B.; Duzenli, C.; Thomas, S.

2014-03-01

Purpose: A system has been developed which recognizes and classifies Digital Imaging and Communication in Medicine contour data with minimal human intervention. It allows researchers to overcome obstacles which tax analysis and mining systems, including inconsistent naming conventions and differences in data age or resolution. Methods: Lexicographic and geometric analysis is used for recognition. Well-known lexicographic methods implemented include Levenshtein-Damerau, bag-of-characters, Double Metaphone, Soundex, and (word and character)-N-grams. Geometrical implementations include 3D Fourier Descriptors, probability spheres, boolean overlap, simple feature comparison (e.g. eccentricity, volume) and rule-based techniques. Both analyses implement custom, domain-specific modules (e.g. emphasis differentiating left/right organ variants). Contour labels from 60 head and neck patients are used for cross-validation. Results: Mixed-lexicographical methods show an effective improvement in more than 10% of recognition attempts compared with a pure Levenshtein-Damerau approach when withholding 70% of the lexicon. Domain-specific and geometrical techniques further boost performance. Conclusions: DICOMautomaton allows users to recognize contours semi-automatically. As usage increases and the lexicon is filled with additional structures, performance improves, increasing the overall utility of the system.

Recognition and defect detection of dot-matrix text via variation-model based learning

NASA Astrophysics Data System (ADS)

Ohyama, Wataru; Suzuki, Koushi; Wakabayashi, Tetsushi

2017-03-01

An algorithm for recognition and defect detection of dot-matrix text printed on products is proposed. Extraction and recognition of dot-matrix text contains several difficulties, which are not involved in standard camera-based OCR, that the appearance of dot-matrix characters is corrupted and broken by illumination, complex texture in the background and other standard characters printed on product packages. We propose a dot-matrix text extraction and recognition method which does not require any user interaction. The method employs detected location of corner points and classification score. The result of evaluation experiment using 250 images shows that recall and precision of extraction are 78.60% and 76.03%, respectively. Recognition accuracy of correctly extracted characters is 94.43%. Detecting printing defect of dot-matrix text is also important in the production scene to avoid illegal productions. We also propose a detection method for printing defect of dot-matrix characters. The method constructs a feature vector of which elements are classification scores of each character class and employs support vector machine to classify four types of printing defect. The detection accuracy of the proposed method is 96.68 %.

Comparison of crisp and fuzzy character networks in handwritten word recognition

NASA Technical Reports Server (NTRS)

Gader, Paul; Mohamed, Magdi; Chiang, Jung-Hsien

1992-01-01

Experiments involving handwritten word recognition on words taken from images of handwritten address blocks from the United States Postal Service mailstream are described. The word recognition algorithm relies on the use of neural networks at the character level. The neural networks are trained using crisp and fuzzy desired outputs. The fuzzy outputs were defined using a fuzzy k-nearest neighbor algorithm. The crisp networks slightly outperformed the fuzzy networks at the character level but the fuzzy networks outperformed the crisp networks at the word level.

Spatial-frequency spectra of printed characters and human visual perception.

PubMed

Põder, Endel

2003-06-01

It is well known that certain spatial frequency (SF) bands are more important than others for character recognition. Solomon and Pelli [Nature 369 (1994) 395-397] have concluded that human pattern recognition mechanism is able to use only a narrow band from available SF spectrum of letters. However, the SF spectra of letters themselves have not been studied carefully. Here I report the results of an analysis of SF spectra of printed characters and discuss their relationship to the observed band-pass nature of letter recognition.

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research.

PubMed

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-Etriby, Sherif

2016-03-11

Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers-that we proposed earlier-improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research

PubMed Central

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-etriby, Sherif

2016-01-01

Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers—that we proposed earlier—improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction. PMID:26978368

Character Recognition Method by Time-Frequency Analyses Using Writing Pressure

NASA Astrophysics Data System (ADS)

Watanabe, Tatsuhito; Katsura, Seiichiro

With the development of information and communication technology, personal verification becomes more and more important. In the future ubiquitous society, the development of terminals handling personal information requires the personal verification technology. The signature is one of the personal verification methods; however, the number of characters is limited in the case of the signature and therefore false signature is used easily. Thus, personal identification is difficult from handwriting. This paper proposes a “haptic pen” that extracts the writing pressure, and shows a character recognition method by time-frequency analyses. Although the figures of characters written by different amanuenses are similar, the differences appear in the time-frequency domain. As a result, it is possible to use the proposed character recognition for personal identification more exactly. The experimental results showed the viability of the proposed method.

Multi-frame knowledge based text enhancement for mobile phone captured videos

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-02-01

In this study, we explore automated text recognition and enhancement using mobile phone captured videos of store receipts. We propose a method which includes Optical Character Resolution (OCR) enhanced by our proposed Row Based Multiple Frame Integration (RB-MFI), and Knowledge Based Correction (KBC) algorithms. In this method, first, the trained OCR engine is used for recognition; then, the RB-MFI algorithm is applied to the output of the OCR. The RB-MFI algorithm determines and combines the most accurate rows of the text outputs extracted by using OCR from multiple frames of the video. After RB-MFI, KBC algorithm is applied to these rows to correct erroneous characters. Results of the experiments show that the proposed video-based approach which includes the RB-MFI and the KBC algorithm increases the word character recognition rate to 95%, and the character recognition rate to 98%.

Combination of dynamic Bayesian network classifiers for the recognition of degraded characters

NASA Astrophysics Data System (ADS)

Likforman-Sulem, Laurence; Sigelle, Marc

2009-01-01

We investigate in this paper the combination of DBN (Dynamic Bayesian Network) classifiers, either independent or coupled, for the recognition of degraded characters. The independent classifiers are a vertical HMM and a horizontal HMM whose observable outputs are the image columns and the image rows respectively. The coupled classifiers, presented in a previous study, associate the vertical and horizontal observation streams into single DBNs. The scores of the independent and coupled classifiers are then combined linearly at the decision level. We compare the different classifiers -independent, coupled or linearly combined- on two tasks: the recognition of artificially degraded handwritten digits and the recognition of real degraded old printed characters. Our results show that coupled DBNs perform better on degraded characters than the linear combination of independent HMM scores. Our results also show that the best classifier is obtained by linearly combining the scores of the best coupled DBN and the best independent HMM.

Notes on Experiments.

ERIC Educational Resources Information Center

Physics Education, 1986

1986-01-01

Describes (1) computer graphics for the coefficient of restitution; (2) an experiment on the optical processing of images; and (3) a simple, coherent optical system for character recognition using Polaroid (Type 665) negative film. (JN)

Integrated system for automated financial document processing

NASA Astrophysics Data System (ADS)

Hassanein, Khaled S.; Wesolkowski, Slawo; Higgins, Ray; Crabtree, Ralph; Peng, Antai

1997-02-01

A system was developed that integrates intelligent document analysis with multiple character/numeral recognition engines in order to achieve high accuracy automated financial document processing. In this system, images are accepted in both their grayscale and binary formats. A document analysis module starts by extracting essential features from the document to help identify its type (e.g. personal check, business check, etc.). These features are also utilized to conduct a full analysis of the image to determine the location of interesting zones such as the courtesy amount and the legal amount. These fields are then made available to several recognition knowledge sources such as courtesy amount recognition engines and legal amount recognition engines through a blackboard architecture. This architecture allows all the available knowledge sources to contribute incrementally and opportunistically to the solution of the given recognition query. Performance results on a test set of machine printed business checks using the integrated system are also reported.

Neural network-based systems for handprint OCR applications.

PubMed

Ganis, M D; Wilson, C L; Blue, J L

1998-01-01

Over the last five years or so, neural network (NN)-based approaches have been steadily gaining performance and popularity for a wide range of optical character recognition (OCR) problems, from isolated digit recognition to handprint recognition. We present an NN classification scheme based on an enhanced multilayer perceptron (MLP) and describe an end-to-end system for form-based handprint OCR applications designed by the National Institute of Standards and Technology (NIST) Visual Image Processing Group. The enhancements to the MLP are based on (i) neuron activations functions that reduce the occurrences of singular Jacobians; (ii) successive regularization to constrain the volume of the weight space; and (iii) Boltzmann pruning to constrain the dimension of the weight space. Performance characterization studies of NN systems evaluated at the first OCR systems conference and the NIST form-based handprint recognition system are also summarized.

Scene Text Recognition using Similarity and a Lexicon with Sparse Belief Propagation

PubMed Central

Weinman, Jerod J.; Learned-Miller, Erik; Hanson, Allen R.

2010-01-01

Scene text recognition (STR) is the recognition of text anywhere in the environment, such as signs and store fronts. Relative to document recognition, it is challenging because of font variability, minimal language context, and uncontrolled conditions. Much information available to solve this problem is frequently ignored or used sequentially. Similarity between character images is often overlooked as useful information. Because of language priors, a recognizer may assign different labels to identical characters. Directly comparing characters to each other, rather than only a model, helps ensure that similar instances receive the same label. Lexicons improve recognition accuracy but are used post hoc. We introduce a probabilistic model for STR that integrates similarity, language properties, and lexical decision. Inference is accelerated with sparse belief propagation, a bottom-up method for shortening messages by reducing the dependency between weakly supported hypotheses. By fusing information sources in one model, we eliminate unrecoverable errors that result from sequential processing, improving accuracy. In experimental results recognizing text from images of signs in outdoor scenes, incorporating similarity reduces character recognition error by 19%, the lexicon reduces word recognition error by 35%, and sparse belief propagation reduces the lexicon words considered by 99.9% with a 12X speedup and no loss in accuracy. PMID:19696446

Liquid lens: advances in adaptive optics

NASA Astrophysics Data System (ADS)

Casey, Shawn Patrick

2010-12-01

'Liquid lens' technologies promise significant advancements in machine vision and optical communications systems. Adaptations for machine vision, human vision correction, and optical communications are used to exemplify the versatile nature of this technology. Utilization of liquid lens elements allows the cost effective implementation of optical velocity measurement. The project consists of a custom image processor, camera, and interface. The images are passed into customized pattern recognition and optical character recognition algorithms. A single camera would be used for both speed detection and object recognition.

Contribution of finger tracing to the recognition of Chinese characters.

PubMed

Yim-Ng, Y Y; Varley, R; Andrade, J

2000-01-01

Finger tracing is a simulation of the act of writing without the use of pen and paper. It is claimed to help in the processing of Chinese characters, possibly by providing additional motor coding. In this study, blindfolded subjects were equally good at identifying Chinese characters and novel visual stimuli through passive movements made with the index finger of the preferred hand and those made with the last finger of that hand. This suggests that finger tracing provides a relatively high level of coding specific to individual characters, but non-specific to motor effectors. Beginning each stroke from the same location, i.e. removing spatial information, impaired recognition of the familiar characters and the novel nonsense figures. Passively tracing the strokes in a random sequence also impaired recognition of the characters. These results therefore suggest that the beneficial effect of finger tracing on writing or recall of Chinese characters is mediated by sequence and spatial information embedded in the motor movements, and that proprioceptive channel may play a part in mediating visuo-spatial information. Finger tracing may be a useful strategy for remediation of Chinese language impairments.

Visual field differences in visual word recognition can emerge purely from perceptual learning: evidence from modeling Chinese character pronunciation.

PubMed

Hsiao, Janet Hui-Wen

2011-11-01

In Chinese orthography, a dominant character structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); a minority opposite arrangement also exists (PS characters). As the number of phonetic radical types is much greater than semantic radical types, in SP characters the information is skewed to the right, whereas in PS characters it is skewed to the left. Through training a computational model for SP and PS character recognition that takes into account of the locations in which the characters appear in the visual field during learning, but does not assume any fundamental hemispheric processing difference, we show that visual field differences can emerge as a consequence of the fundamental structural differences in information between SP and PS characters, as opposed to the fundamental processing differences between the two hemispheres. This modeling result is also consistent with behavioral naming performance. This work provides strong evidence that perceptual learning, i.e., the information structure of word stimuli to which the readers have long been exposed, is one of the factors that accounts for hemispheric asymmetry effects in visual word recognition. Copyright © 2011 Elsevier Inc. All rights reserved.

A segmentation-free approach to Arabic and Urdu OCR

NASA Astrophysics Data System (ADS)

Sabbour, Nazly; Shafait, Faisal

2013-01-01

In this paper, we present a generic Optical Character Recognition system for Arabic script languages called Nabocr. Nabocr uses OCR approaches specific for Arabic script recognition. Performing recognition on Arabic script text is relatively more difficult than Latin text due to the nature of Arabic script, which is cursive and context sensitive. Moreover, Arabic script has different writing styles that vary in complexity. Nabocr is initially trained to recognize both Urdu Nastaleeq and Arabic Naskh fonts. However, it can be trained by users to be used for other Arabic script languages. We have evaluated our system's performance for both Urdu and Arabic. In order to evaluate Urdu recognition, we have generated a dataset of Urdu text called UPTI (Urdu Printed Text Image Database), which measures different aspects of a recognition system. The performance of our system for Urdu clean text is 91%. For Arabic clean text, the performance is 86%. Moreover, we have compared the performance of our system against Tesseract's newly released Arabic recognition, and the performance of both systems on clean images is almost the same.

Post processing of optically recognized text via second order hidden Markov model

NASA Astrophysics Data System (ADS)

Poudel, Srijana

In this thesis, we describe a postprocessing system on Optical Character Recognition(OCR) generated text. Second Order Hidden Markov Model (HMM) approach is used to detect and correct the OCR related errors. The reason for choosing the 2nd order HMM is to keep track of the bigrams so that the model can represent the system more accurately. Based on experiments with training data of 159,733 characters and testing of 5,688 characters, the model was able to correct 43.38 % of the errors with a precision of 75.34 %. However, the precision value indicates that the model introduced some new errors, decreasing the correction percentage to 26.4%.

Teach Your Computer to Read: Scanners and Optical Character Recognition.

ERIC Educational Resources Information Center

Marsden, Jim

1993-01-01

Desktop scanners can be used with a software technology called optical character recognition (OCR) to convert the text on virtually any paper document into an electronic form. OCR offers educators new flexibility in incorporating text into tests, lesson plans, and other materials. (MLF)

Optical character recognition reading aid for the visually impaired.

PubMed

Grandin, Juan Carlos; Cremaschi, Fabian; Lombardo, Elva; Vitu, Ed; Dujovny, Manuel

2008-06-01

An optical character recognition (OCR) reading machine is a significant help for visually impaired patients. An OCR reading machine is used. This instrument can provide a significant help in order to improve the quality of life of patients with low vision or blindness.

Chinese Children's Character Recognition: Visuo-Orthographic, Phonological Processing and Morphological Skills

ERIC Educational Resources Information Center

Li, Hong; Shu, Hua; McBride-Chang, Catherine; Liu, Hongyun; Peng, Hong

2012-01-01

Tasks tapping visual skills, orthographic knowledge, phonological awareness, speeded naming, morphological awareness and Chinese character recognition were administered to 184 kindergarteners and 273 primary school students from Beijing. Regression analyses indicated that only syllable deletion, morphological construction and speeded number naming…

Image simulation for automatic license plate recognition

NASA Astrophysics Data System (ADS)

Bala, Raja; Zhao, Yonghui; Burry, Aaron; Kozitsky, Vladimir; Fillion, Claude; Saunders, Craig; Rodríguez-Serrano, José

2012-01-01

Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.

A Horizontal Tilt Correction Method for Ship License Numbers Recognition

NASA Astrophysics Data System (ADS)

Liu, Baolong; Zhang, Sanyuan; Hong, Zhenjie; Ye, Xiuzi

2018-02-01

An automatic ship license numbers (SLNs) recognition system plays a significant role in intelligent waterway transportation systems since it can be used to identify ships by recognizing the characters in SLNs. Tilt occurs frequently in many SLNs because the monitors and the ships usually have great vertical or horizontal angles, which decreases the accuracy and robustness of a SLNs recognition system significantly. In this paper, we present a horizontal tilt correction method for SLNs. For an input tilt SLN image, the proposed method accomplishes the correction task through three main steps. First, a MSER-based characters’ center-points computation algorithm is designed to compute the accurate center-points of the characters contained in the input SLN image. Second, a L 1- L 2 distance-based straight line is fitted to the computed center-points using M-estimator algorithm. The tilt angle is estimated at this stage. Finally, based on the computed tilt angle, an affine transformation rotation is conducted to rotate and to correct the input SLN horizontally. At last, the proposed method is tested on 200 tilt SLN images, the proposed method is proved to be effective with a tilt correction rate of 80.5%.

Optical character recognition with feature extraction and associative memory matrix

NASA Astrophysics Data System (ADS)

Sasaki, Osami; Shibahara, Akihito; Suzuki, Takamasa

1998-06-01

A method is proposed in which handwritten characters are recognized using feature extraction and an associative memory matrix. In feature extraction, simple processes such as shifting and superimposing patterns are executed. A memory matrix is generated with singular value decomposition and by modifying small singular values. The method is optically implemented with two liquid crystal displays. Experimental results for the recognition of 25 handwritten alphabet characters clearly shows the effectiveness of the method.

Do dyslexic individuals present a reduced visual attention span? Evidence from visual recognition tasks of non-verbal multi-character arrays.

PubMed

Yeari, Menahem; Isser, Michal; Schiff, Rachel

2017-07-01

A controversy has recently developed regarding the hypothesis that developmental dyslexia may be caused, in some cases, by a reduced visual attention span (VAS). To examine this hypothesis, independent of phonological abilities, researchers tested the ability of dyslexic participants to recognize arrays of unfamiliar visual characters. Employing this test, findings were rather equivocal: dyslexic participants exhibited poor performance in some studies but normal performance in others. The present study explored four methodological differences revealed between the two sets of studies that might underlie their conflicting results. Specifically, in two experiments we examined whether a VAS deficit is (a) specific to recognition of multi-character arrays as wholes rather than of individual characters within arrays, (b) specific to characters' position within arrays rather than to characters' identity, or revealed only under a higher attention load due to (c) low-discriminable characters, and/or (d) characters' short exposure. Furthermore, in this study we examined whether pure dyslexic participants who do not have attention disorder exhibit a reduced VAS. Although comorbidity of dyslexia and attention disorder is common and the ability to sustain attention for a long time plays a major rule in the visual recognition task, the presence of attention disorder was neither evaluated nor ruled out in previous studies. Findings did not reveal any differences between the performance of dyslexic and control participants on eight versions of the visual recognition task. These findings suggest that pure dyslexic individuals do not present a reduced visual attention span.

A study of payload specialist station monitor size constraints. [space shuttle orbiters

NASA Technical Reports Server (NTRS)

Kirkpatrick, M., III; Shields, N. L., Jr.; Malone, T. B.

1975-01-01

Constraints on the CRT display size for the shuttle orbiter cabin are studied. The viewing requirements placed on these monitors were assumed to involve display of imaged scenes providing visual feedback during payload operations and display of alphanumeric characters. Data on target recognition/resolution, target recognition, and range rate detection by human observers were utilized to determine viewing requirements for imaged scenes. Field-of-view and acuity requirements for a variety of payload operations were obtained along with the necessary detection capability in terms of range-to-target size ratios. The monitor size necessary to meet the acuity requirements was established. An empirical test was conducted to determine required recognition sizes for displayed alphanumeric characters. The results of the test were used to determine the number of characters which could be simultaneously displayed based on the recognition size requirements using the proposed monitor size. A CRT display of 20 x 20 cm is recommended. A portion of the display area is used for displaying imaged scenes and the remaining display area is used for alphanumeric characters pertaining to the displayed scene. The entire display is used for the character alone mode.

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

PubMed

Sadeghi, Zahra; Testolin, Alberto

2017-08-01

In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

The Inversion Effect for Chinese Characters is Modulated by Radical Organization.

PubMed

Luo, Canhuang; Chen, Wei; Zhang, Ye

2017-06-01

In studies of visual object recognition, strong inversion effects accompany the acquisition of expertise and imply the involvement of configural processing. Chinese literacy results in sensitivity to the orthography of Chinese characters. While there is some evidence that this orthographic sensitivity results in an inversion effect, and thus involves configural processing, that processing might depend on exact orthographic properties. Chinese character recognition is believed to involve a hierarchical process, involving at least two lower levels of representation: strokes and radicals. Radicals are grouped into characters according to certain types of structure, i.e. left-right structure, top-bottom structure, or simple characters with only one radical by itself. These types of radical structures vary in both familiarity, and in hierarchical level (compound versus simple characters). In this study, we investigate whether the hierarchical-level or familiarity of radical-structure has an impact on the magnitude of the inversion effect. Participants were asked to do a matching task on pairs of either upright or inverted characters with all the types of structure. Inversion effects were measured based on both reaction time and response sensitivity. While an inversion effect was observed in all 3 conditions, the magnitude of the inversion effect varied with radical structure, being significantly larger for the most familiar type of structure: characters consisting of 2 radicals organized from left to right. These findings indicate that character recognition involves extraction of configural structure as well as radical processing which play different roles in the processing of compound characters and simple characters.

Does the cost function matter in Bayes decision rule?

PubMed

Schlü ter, Ralf; Nussbaum-Thom, Markus; Ney, Hermann

2012-02-01

In many tasks in pattern recognition, such as automatic speech recognition (ASR), optical character recognition (OCR), part-of-speech (POS) tagging, and other string recognition tasks, we are faced with a well-known inconsistency: The Bayes decision rule is usually used to minimize string (symbol sequence) error, whereas, in practice, we want to minimize symbol (word, character, tag, etc.) error. When comparing different recognition systems, we do indeed use symbol error rate as an evaluation measure. The topic of this work is to analyze the relation between string (i.e., 0-1) and symbol error (i.e., metric, integer valued) cost functions in the Bayes decision rule, for which fundamental analytic results are derived. Simple conditions are derived for which the Bayes decision rule with integer-valued metric cost function and with 0-1 cost gives the same decisions or leads to classes with limited cost. The corresponding conditions can be tested with complexity linear in the number of classes. The results obtained do not make any assumption w.r.t. the structure of the underlying distributions or the classification problem. Nevertheless, the general analytic results are analyzed via simulations of string recognition problems with Levenshtein (edit) distance cost function. The results support earlier findings that considerable improvements are to be expected when initial error rates are high.

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.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

PubMed

Bahlmann, Claus; Burkhardt, Hans

2004-03-01

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

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.

Perceptual expertise: can sensorimotor experience change holistic processing and left-side bias?

PubMed

Tso, Ricky Van-yip; Au, Terry Kit-fong; Hsiao, Janet Hui-wen

2014-09-01

Holistic processing and left-side bias are both behavioral markers of expert face recognition. By contrast, expert recognition of characters in Chinese orthography involves left-side bias but reduced holistic processing, although faces and Chinese characters share many visual properties. Here, we examined whether this reduction in holistic processing of Chinese characters can be better explained by writing experience than by reading experience. Compared with Chinese nonreaders, Chinese readers who had limited writing experience showed increased holistic processing, whereas Chinese readers who could write characters fluently showed reduced holistic processing. This result suggests that writing and sensorimotor experience can modulate holistic-processing effects and that the reduced holistic processing observed in expert Chinese readers may depend mostly on writing experience. However, both expert writers and writers with limited experience showed similarly stronger left-side bias than novices did in processing mirror-symmetric Chinese characters; left-side bias may therefore be a robust expertise marker for object recognition that is uninfluenced by sensorimotor experience. © The Author(s) 2014.

Kansas State University Libraries' OCR Labeling Project.

ERIC Educational Resources Information Center

Thierer, Joyce; Bower, Merry

This publication describes the planning and implementation of an optical character recognition (OCR) labeling project, the first stage of Kansas State University (KSU) Libraries' program of conversion from a manual to an automated circulation system. It is noted that a telephone survey of libraries with automated circulation systems and…

Electronic Information Delivery Systems: Reports on Five Projects Sponsored by the Fred Meyer Charitable Trust.

ERIC Educational Resources Information Center

Ferguson, Douglas K.; And Others

1987-01-01

Describes five research projects that are setting up electronic information delivery systems to serve rural areas in the Pacific Northwest. The technologies being evaluated include simultaneous remote searching, facsimile transmissions, bit map image transmissions, and a combination of optical character recognition equipment and television…

Boost OCR accuracy using iVector based system combination approach

NASA Astrophysics Data System (ADS)

Peng, Xujun; Cao, Huaigu; Natarajan, Prem

2015-01-01

Optical character recognition (OCR) is a challenging task because most existing preprocessing approaches are sensitive to writing style, writing material, noises and image resolution. Thus, a single recognition system cannot address all factors of real document images. In this paper, we describe an approach to combine diverse recognition systems by using iVector based features, which is a newly developed method in the field of speaker verification. Prior to system combination, document images are preprocessed and text line images are extracted with different approaches for each system, where iVector is transformed from a high-dimensional supervector of each text line and is used to predict the accuracy of OCR. We merge hypotheses from multiple recognition systems according to the overlap ratio and the predicted OCR score of text line images. We present evaluation results on an Arabic document database where the proposed method is compared against the single best OCR system using word error rate (WER) metric.

Slant rectification in Russian passport OCR system using fast Hough transform

NASA Astrophysics Data System (ADS)

Limonova, Elena; Bezmaternykh, Pavel; Nikolaev, Dmitry; Arlazarov, Vladimir

2017-03-01

In this paper, we introduce slant detection method based on Fast Hough Transform calculation and demonstrate its application in industrial system for Russian passports recognition. About 1.5% of this kind of documents appear to be slant or italic. This fact reduces recognition rate, because Optical Recognition Systems are normally designed to process normal fonts. Our method uses Fast Hough Transform to analyse vertical strokes of characters extracted with the help of x-derivative of a text line image. To improve the quality of detector we also introduce field grouping rules. The resulting algorithm allowed to reach high detection quality. Almost all errors of considered approach happen on passports of nonstandard fonts, while slant detector works in appropriate way.

Visual Similarity of Words Alone Can Modulate Hemispheric Lateralization in Visual Word Recognition: Evidence From Modeling Chinese Character Recognition.

PubMed

Hsiao, Janet H; Cheung, Kit

2016-03-01

In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right (SP characters); the minority, opposite arrangement also exists (PS characters). Recent studies showed that SP character processing is more left hemisphere (LH) lateralized than PS character processing. Nevertheless, it remains unclear whether this is due to phonetic radical position or character type frequency. Through computational modeling with artificial lexicons, in which we implement a theory of hemispheric asymmetry in perception but do not assume phonological processing being LH lateralized, we show that the difference in character type frequency alone is sufficient to exhibit the effect that the dominant type has a stronger LH lateralization than the minority type. This effect is due to higher visual similarity among characters in the dominant type than the minority type, demonstrating the modulation of visual similarity of words on hemispheric lateralization. Copyright © 2015 Cognitive Science Society, Inc.

Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency.

PubMed

Lin, Nan; Yu, Xi; Zhao, Ying; Zhang, Mingxia

2016-01-01

This fMRI study aimed to identify the neural mechanisms underlying the recognition of Chinese multi-character words by partialling out the confounding effect of reaction time (RT). For this purpose, a special type of nonword-transposable nonword-was created by reversing the character orders of real words. These nonwords were included in a lexical decision task along with regular (non-transposable) nonwords and real words. Through conjunction analysis on the contrasts of transposable nonwords versus regular nonwords and words versus regular nonwords, the confounding effect of RT was eliminated, and the regions involved in word recognition were reliably identified. The word-frequency effect was also examined in emerged regions to further assess their functional roles in word processing. Results showed significant conjunctional effect and positive word-frequency effect in the bilateral inferior parietal lobules and posterior cingulate cortex, whereas only conjunctional effect was found in the anterior cingulate cortex. The roles of these brain regions in recognition of Chinese multi-character words were discussed.

Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency

PubMed Central

Lin, Nan; Yu, Xi; Zhao, Ying; Zhang, Mingxia

2016-01-01

This fMRI study aimed to identify the neural mechanisms underlying the recognition of Chinese multi-character words by partialling out the confounding effect of reaction time (RT). For this purpose, a special type of nonword—transposable nonword—was created by reversing the character orders of real words. These nonwords were included in a lexical decision task along with regular (non-transposable) nonwords and real words. Through conjunction analysis on the contrasts of transposable nonwords versus regular nonwords and words versus regular nonwords, the confounding effect of RT was eliminated, and the regions involved in word recognition were reliably identified. The word-frequency effect was also examined in emerged regions to further assess their functional roles in word processing. Results showed significant conjunctional effect and positive word-frequency effect in the bilateral inferior parietal lobules and posterior cingulate cortex, whereas only conjunctional effect was found in the anterior cingulate cortex. The roles of these brain regions in recognition of Chinese multi-character words were discussed. PMID:26901644

Noisy text categorization.

PubMed

Vinciarelli, Alessandro

2005-12-01

This work presents categorization experiments performed over noisy texts. By noisy, we mean any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g., transcriptions of speech recordings extracted with a recognition system). The performance of a categorization system over the clean and noisy (Word Error Rate between approximately 10 and approximately 50 percent) versions of the same documents is compared. The noisy texts are obtained through handwriting recognition and simulation of optical character recognition. The results show that the performance loss is acceptable for Recall values up to 60-70 percent depending on the noise sources. New measures of the extraction process performance, allowing a better explanation of the categorization results, are proposed.

Handprinted Forms and Characters

National Institute of Standards and Technology Data Gateway

NIST Handprinted Forms and Characters (Web, free access)   NIST Special Database 19 contains NIST's entire corpus of training materials for handprinted document and character recognition. It supersedes NIST Special Databases 3 and 7.

Personality and emotion-based high-level control of affective story characters.

PubMed

Su, Wen-Poh; Pham, Binh; Wardhani, Aster

2007-01-01

Human emotional behavior, personality, and body language are the essential elements in the recognition of a believable synthetic story character. This paper presents an approach using story scripts and action descriptions in a form similar to the content description of storyboards to predict specific personality and emotional states. By adopting the Abridged Big Five Circumplex (AB5C) Model of personality from the study of psychology as a basis for a computational model, we construct a hierarchical fuzzy rule-based system to facilitate the personality and emotion control of the body language of a dynamic story character. The story character can consistently perform specific postures and gestures based on his/her personality type. Story designers can devise a story context in the form of our story interface which predictably motivates personality and emotion values to drive the appropriate movements of the story characters. Our system takes advantage of relevant knowledge described by psychologists and researchers of storytelling, nonverbal communication, and human movement. Our ultimate goal is to facilitate the high-level control of a synthetic character.

Neural substrates of Hanja (Logogram) and Hangul (Phonogram) character readings by functional magnetic resonance imaging.

PubMed

Cho, Zang-Hee; Kim, Nambeom; Bae, Sungbong; Chi, Je-Geun; Park, Chan-Woong; Ogawa, Seiji; Kim, Young-Bo

2014-10-01

The two basic scripts of the Korean writing system, Hanja (the logography of the traditional Korean character) and Hangul (the more newer Korean alphabet), have been used together since the 14th century. While Hanja character has its own morphemic base, Hangul being purely phonemic without morphemic base. These two, therefore, have substantially different outcomes as a language as well as different neural responses. Based on these linguistic differences between Hanja and Hangul, we have launched two studies; first was to find differences in cortical activation when it is stimulated by Hanja and Hangul reading to support the much discussed dual-route hypothesis of logographic and phonological routes in the brain by fMRI (Experiment 1). The second objective was to evaluate how Hanja and Hangul affect comprehension, therefore, recognition memory, specifically the effects of semantic transparency and morphemic clarity on memory consolidation and then related cortical activations, using functional magnetic resonance imaging (fMRI) (Experiment 2). The first fMRI experiment indicated relatively large areas of the brain are activated by Hanja reading compared to Hangul reading. The second experiment, the recognition memory study, revealed two findings, that is there is only a small difference in recognition memory for semantic transparency, while for the morphemic clarity was much larger between Hanja and Hangul. That is the morphemic clarity has significantly more effect than semantic transparency on recognition memory when studies by fMRI in correlation with behavioral study.

The role of lexical variables in the visual recognition of Chinese characters: A megastudy analysis.

PubMed

Sze, Wei Ping; Yap, Melvin J; Rickard Liow, Susan J

2015-01-01

Logographic Chinese orthography partially represents both phonology and semantics. By capturing the online processing of a large pool of Chinese characters, we were able to examine the relative salience of specific lexical variables when this nonalphabetic script is read. Using a sample of native mainland Chinese speakers (N = 35), lexical decision latencies for 1560 single characters were collated into a database, before the effects of a comprehensive range of variables were explored. Hierarchical regression analyses determined the unique item-level variance explained by orthographic (frequency, stroke count), semantic (age of learning, imageability, number of meanings), and phonological (consistency, phonological frequency) factors. Orthographic and semantic variables, respectively, accounted for more collective variance than the phonological variables. Significant main effects were further observed for the individual orthographic and semantic predictors. These results are consistent with the idea that skilled readers tend to rely on orthographic and semantic information when processing visually presented characters. This megastudy approach marks an important extension to existing work on Chinese character recognition, which hitherto has relied on factorial designs. Collectively, the findings reported here represent a useful set of empirical constraints for future computational models of character recognition.

Jersey number detection in sports video for athlete identification

NASA Astrophysics Data System (ADS)

Ye, Qixiang; Huang, Qingming; Jiang, Shuqiang; Liu, Yang; Gao, Wen

2005-07-01

Athlete identification is important for sport video content analysis since users often care about the video clips with their preferred athletes. In this paper, we propose a method for athlete identification by combing the segmentation, tracking and recognition procedures into a coarse-to-fine scheme for jersey number (digital characters on sport shirt) detection. Firstly, image segmentation is employed to separate the jersey number regions with its background. And size/pipe-like attributes of digital characters are used to filter out candidates. Then, a K-NN (K nearest neighbor) classifier is employed to classify a candidate into a digit in "0-9" or negative. In the recognition procedure, we use the Zernike moment features, which are invariant to rotation and scale for digital shape recognition. Synthetic training samples with different fonts are used to represent the pattern of digital characters with non-rigid deformation. Once a character candidate is detected, a SSD (smallest square distance)-based tracking procedure is started. The recognition procedure is performed every several frames in the tracking process. After tracking tens of frames, the overall recognition results are combined to determine if a candidate is a true jersey number or not by a voting procedure. Experiments on several types of sports video shows encouraging result.

Recognizing Chinese characters in digital ink from non-native language writers using hierarchical models

NASA Astrophysics Data System (ADS)

Bai, Hao; Zhang, Xi-wen

2017-06-01

While Chinese is learned as a second language, its characters are taught step by step from their strokes to components, radicals to components, and their complex relations. Chinese Characters in digital ink from non-native language writers are deformed seriously, thus the global recognition approaches are poorer. So a progressive approach from bottom to top is presented based on hierarchical models. Hierarchical information includes strokes and hierarchical components. Each Chinese character is modeled as a hierarchical tree. Strokes in one Chinese characters in digital ink are classified with Hidden Markov Models and concatenated to the stroke symbol sequence. And then the structure of components in one ink character is extracted. According to the extraction result and the stroke symbol sequence, candidate characters are traversed and scored. Finally, the recognition candidate results are listed by descending. The method of this paper is validated by testing 19815 copies of the handwriting Chinese characters written by foreign students.

Arabic OCR: toward a complete system

NASA Astrophysics Data System (ADS)

El-Bialy, Ahmed M.; Kandil, Ahmed H.; Hashish, Mohamed; Yamany, Sameh M.

1999-12-01

Latin and Chinese OCR systems have been studied extensively in the literature. Yet little work was performed for Arabic character recognition. This is due to the technical challenges found in the Arabic text. Due to its cursive nature, a powerful and stable text segmentation is needed. Also; features capturing the characteristics of the rich Arabic character representation are needed to build the Arabic OCR. In this paper a novel segmentation technique which is font and size independent is introduced. This technique can segment the cursive written text line even if the line suffers from small skewness. The technique is not sensitive to the location of the centerline of the text line and can segment different font sizes and type (for different character sets) occurring on the same line. Features extraction is considered one of the most important phases of the text reading system. Ideally, the features extracted from a character image should capture the essential characteristics of this character that are independent of the font type and size. In such ideal case, the classifier stores a single prototype per character. However, it is practically challenging to find such ideal set of features. In this paper, a set of features that reflect the topological aspects of Arabia characters is proposed. These proposed features integrated with a topological matching technique introduce an Arabic text reading system that is semi Omni.

The Heinz Electronic Library Interactive On-line System (HELIOS): An Update.

ERIC Educational Resources Information Center

Galloway, Edward A.; Michalek, Gabrielle V.

1998-01-01

Describes a project at Carnegie Mellon University libraries to convert the congressional papers of the late Senator John Heinz to digital format and to create an online system to search and retrieve these papers. Highlights include scanning, optical character recognition, and a search engine utilizing natural language processing. (Author/LRW)

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

PubMed Central

Wu, Jei-Tun

2016-01-01

In psycholinguistic research, the frequency effect can be one of the indicators for eligible experimental tasks that examine the nature of lexical access. Usually, only one of those tasks is chosen to examine lexical access in a study. Using two exemplar experiments, this paper introduces an approach to include both the lexical decision task and the naming task in a study. In the first experiment, the stimuli were Chinese characters with frequency and regularity manipulated. In the second experiment, the stimuli were switched to Chinese two-character words, in which the word frequency and the regularity of the leading character were manipulated. The logic of these two exemplar experiments was to explore some important issues such as the role of phonology on recognition by comparing the frequency effect between both the tasks. The results revealed different patterns of lexical access from those reported in the alphabetic systems. The results of Experiment 1 manifested a larger frequency effect in the naming task as compared to the LDT, when the stimuli were Chinese characters. And it is noteworthy that, in Experiment 1, when the stimuli were regular Chinese characters, the frequency effect observed in the naming task was roughly equivalent to that in the LDT. However, a smaller frequency effect was shown in the naming task as compared to the LDT, when the stimuli were switched to Chinese two-character words in Experiment 2. Taking advantage of the respective demands and characteristics in both tasks, researchers can obtain a more complete and precise picture of character/word recognition. PMID:27077703

Digitization of Full-Text Documents Before Publishing on the Internet: A Case Study Reviewing the Latest Optical Character Recognition Technologies.

ERIC Educational Resources Information Center

McClean, Clare M.

1998-01-01

Reviews strengths and weaknesses of five optical character recognition (OCR) software packages used to digitize paper documents before publishing on the Internet. Outlines options available and stages of the conversion process. Describes the learning experience of Eurotext, a United Kingdom-based electronic libraries project (eLib). (PEN)

Preliminary Study of the Effect of Incremental Rehearsal with a Morphological Component for Teaching Chinese Character Recognition

ERIC Educational Resources Information Center

Kwong, Elena; Burns, Matthew K.

2016-01-01

The current study examined the effectiveness of Incremental Rehearsal (IR) for teaching Chinese character recognition using a single-case experimental design. In addition, a morphological component was added to standard IR procedures (IRM) to take into account the role of morphological awareness in Chinese reading. Three kindergarten students in…

Morphological Structure Processing during Word Recognition and Its Relationship to Character Reading among Third-Grade Chinese Children

ERIC Educational Resources Information Center

Liu, Duo; McBride-Chang, Catherine

2014-01-01

In the present study, we explored the characteristics of morphological structure processing during word recognition among third grade Chinese children and its possible relationship with Chinese character reading. By using the modified priming lexical decision paradigm, a significant morphological structure priming effect was found in the subject…

Structural model constructing for optical handwritten character recognition

NASA Astrophysics Data System (ADS)

Khaustov, P. A.; Spitsyn, V. G.; Maksimova, E. I.

2017-02-01

The article is devoted to the development of the algorithms for optical handwritten character recognition based on the structural models constructing. The main advantage of these algorithms is the low requirement regarding the number of reference images. The one-pass approach to a thinning of the binary character representation has been proposed. This approach is based on the joint use of Zhang-Suen and Wu-Tsai algorithms. The effectiveness of the proposed approach is confirmed by the results of the experiments. The article includes the detailed description of the structural model constructing algorithm’s steps. The proposed algorithm has been implemented in character processing application and has been approved on MNIST handwriting characters database. Algorithms that could be used in case of limited reference images number were used for the comparison.

Radical Sensitivity Is the Key to Understanding Chinese Character Acquisition in Children

ERIC Educational Resources Information Center

Tong, Xiuhong; Tong, Xiuli; McBride, Catherine

2017-01-01

This study investigated Chinese children's development of sensitivity to positional (orthographic), phonological, and semantic cues of radicals in encoding novel Chinese characters. A newly designed picture-novel character mapping task, along with nonverbal reasoning ability, vocabulary, and Chinese character recognition were administered to 198…

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

The Impact of a Modified Repeated-Reading Strategy Paired with Optical Character Recognition on the Reading Rates of Students with Visual Impairments

ERIC Educational Resources Information Center

Pattillo, Suzan Trefry; Heller, Kathryn Wolf; Smith, Maureen

2004-01-01

The repeated-reading strategy and optical character recognition were paired to demonstrate a functional relationship between the combined strategies and two factors: the reading rates of students with visual impairments and the students' self-perceptions, or attitudes, toward reading. The results indicated that all five students increased their…

Native-Language Phonological Interference in Early Hakka-Mandarin Bilinguals' Visual Recognition of Chinese Two-Character Compounds: Evidence from the Semantic-Relatedness Decision Task

ERIC Educational Resources Information Center

Wu, Shiyu; Ma, Zheng

2017-01-01

Previous research has indicated that, in viewing a visual word, the activated phonological representation in turn activates its homophone, causing semantic interference. Using this mechanism of phonological mediation, this study investigated native-language phonological interference in visual recognition of Chinese two-character compounds by early…

Toward a Graded Psycholexical Space Mapping Model: Sublexical and Lexical Representations in Chinese Character Reading Development.

PubMed

Tong, Xiuli; McBride, Catherine

2017-07-01

Following a review of contemporary models of word-level processing for reading and their limitations, we propose a new hypothetical model of Chinese character reading, namely, the graded lexical space mapping model that characterizes how sublexical radicals and lexical information are involved in Chinese character reading development. The underlying assumption of this model is that Chinese character recognition is a process of competitive mappings of phonology, semantics, and orthography in both lexical and sublexical systems, operating as functions of statistical properties of print input based on the individual's specific level of reading. This model leads to several testable predictions concerning how the quasiregularity and continuity of Chinese-specific radicals are organized in memory for both child and adult readers at different developmental stages of reading.

OCR Scanners Facilitate WP Training in Business Schools and Colleges.

ERIC Educational Resources Information Center

School Business Affairs, 1983

1983-01-01

Optical Character Recognition Scanners (OCR) scan typed text and feed it directly into word processing systems, saving input time. OCRs are valuable in word processing training programs because they allow more students access to classes and more time for skill training. (MD)

Document recognition serving people with disabilities

NASA Astrophysics Data System (ADS)

Fruchterman, James R.

2007-01-01

Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.

PubMed

Yang, Cheng-Huei; Luo, Ching-Hsing; Yang, Cheng-Hong; Chuang, Li-Yeh

2004-01-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.

Reading as Active Sensing: A Computational Model of Gaze Planning in Word Recognition

PubMed Central

Ferro, Marcello; Ognibene, Dimitri; Pezzulo, Giovanni; Pirrelli, Vito

2010-01-01

We offer a computational model of gaze planning during reading that consists of two main components: a lexical representation network, acquiring lexical representations from input texts (a subset of the Italian CHILDES database), and a gaze planner, designed to recognize written words by mapping strings of characters onto lexical representations. The model implements an active sensing strategy that selects which characters of the input string are to be fixated, depending on the predictions dynamically made by the lexical representation network. We analyze the developmental trajectory of the system in performing the word recognition task as a function of both increasing lexical competence, and correspondingly increasing lexical prediction ability. We conclude by discussing how our approach can be scaled up in the context of an active sensing strategy applied to a robotic setting. PMID:20577589

Reading as active sensing: a computational model of gaze planning in word recognition.

PubMed

Ferro, Marcello; Ognibene, Dimitri; Pezzulo, Giovanni; Pirrelli, Vito

2010-01-01

WE OFFER A COMPUTATIONAL MODEL OF GAZE PLANNING DURING READING THAT CONSISTS OF TWO MAIN COMPONENTS: a lexical representation network, acquiring lexical representations from input texts (a subset of the Italian CHILDES database), and a gaze planner, designed to recognize written words by mapping strings of characters onto lexical representations. The model implements an active sensing strategy that selects which characters of the input string are to be fixated, depending on the predictions dynamically made by the lexical representation network. We analyze the developmental trajectory of the system in performing the word recognition task as a function of both increasing lexical competence, and correspondingly increasing lexical prediction ability. We conclude by discussing how our approach can be scaled up in the context of an active sensing strategy applied to a robotic setting.

Character recognition from trajectory by recurrent spiking neural networks.

PubMed

Jiangrong Shen; Kang Lin; Yueming Wang; Gang Pan

2017-07-01

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.

An Autonomous Learning System of Bengali Characters Using Web-Based Intelligent Handwriting Recognition

ERIC Educational Resources Information Center

Khatun, Nazma; Miwa, Jouji

2016-01-01

This research project was aimed to develop an intelligent Bengali handwriting education system to improve the literacy level in Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. Here, we developed a prototype of web-based (iPhone/smartphone or computer browser) intelligent…

Are we there yet?

PubMed

Cristianini, Nello

2010-05-01

Statistical approaches to Artificial Intelligence are behind most success stories of the field in the past decade. The idea of generating non-trivial behaviour by analysing vast amounts of data has enabled recommendation systems, search engines, spam filters, optical character recognition, machine translation and speech recognition, among other things. As we celebrate the spectacular achievements of this line of research, we need to assess its full potential and its limitations. What are the next steps to take towards machine intelligence? 2010 Elsevier Ltd. All rights reserved.

Electrophysiological evidence of sublexical phonological access in character processing by L2 Chinese learners of L1 alphabetic scripts.

PubMed

Yum, Yen Na; Law, Sam-Po; Mo, Kwan Nok; Lau, Dustin; Su, I-Fan; Shum, Mark S K

2016-04-01

While Chinese character reading relies more on addressed phonology relative to alphabetic scripts, skilled Chinese readers also access sublexical phonological units during recognition of phonograms. However, sublexical orthography-to-phonology mapping has not been found among beginning second language (L2) Chinese learners. This study investigated character reading in more advanced Chinese learners whose native writing system is alphabetic. Phonological regularity and consistency were examined in behavioral responses and event-related potentials (ERPs) in lexical decision and delayed naming tasks. Participants were 18 native English speakers who acquired written Chinese after age 5 years and reached grade 4 Chinese reading level. Behaviorally, regular characters were named more accurately than irregular characters, but consistency had no effect. Similar to native Chinese readers, regularity effects emerged early with regular characters eliciting a greater N170 than irregular characters. Regular characters also elicited greater frontal P200 and smaller N400 than irregular characters in phonograms of low consistency. Additionally, regular-consistent characters and irregular-inconsistent characters had more negative amplitudes than irregular-consistent characters in the N400 and LPC time windows. The overall pattern of brain activities revealed distinct regularity and consistency effects in both tasks. Although orthographic neighbors are activated in character processing of L2 Chinese readers, the timing of their impact seems delayed compared with native Chinese readers. The time courses of regularity and consistency effects across ERP components suggest both assimilation and accommodation of the reading network in learning to read a typologically distinct second orthographic system.

Performance-Driven Hybrid Full-Body Character Control for Navigation and Interaction in Virtual Environments

NASA Astrophysics Data System (ADS)

Mousas, Christos; Anagnostopoulos, Christos-Nikolaos

2017-06-01

This paper presents a hybrid character control interface that provides the ability to synthesize in real-time a variety of actions based on the user's performance capture. The proposed methodology enables three different performance interaction modules: the performance animation control that enables the direct mapping of the user's pose to the character, the motion controller that synthesizes the desired motion of the character based on an activity recognition methodology, and the hybrid control that lies within the performance animation and the motion controller. With the methodology presented, the user will have the freedom to interact within the virtual environment, as well as the ability to manipulate the character and to synthesize a variety of actions that cannot be performed directly by him/her, but which the system synthesizes. Therefore, the user is able to interact with the virtual environment in a more sophisticated fashion. This paper presents examples of different scenarios based on the three different full-body character control methodologies.

The JSTOR Solution: Accessing and Preserving the Past.

ERIC Educational Resources Information Center

Guthrie, Kevin M.; Lougee, Wendy P.

1997-01-01

Describes JSTOR (Journal Storage), a not-for-profit organization located in New York City, established to use digital technology to preserve and make accessible core journal literature. Highlights include publisher participation and license agreements; scanning and optical character recognition; missing information; systems design; project goals;…

Visual Field Differences in Visual Word Recognition Can Emerge Purely from Perceptual Learning: Evidence from Modeling Chinese Character Pronunciation

ERIC Educational Resources Information Center

Hsiao, Janet Hui-wen

2011-01-01

In Chinese orthography, a dominant character structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); a minority opposite arrangement also exists (PS characters). As the number of phonetic radical types is much greater than semantic radical types, in SP characters the information is…

ESARR: enhanced situational awareness via road sign recognition

NASA Astrophysics Data System (ADS)

Perlin, V. E.; Johnson, D. B.; Rohde, M. M.; Lupa, R. M.; Fiorani, G.; Mohammad, S.

2010-04-01

The enhanced situational awareness via road sign recognition (ESARR) system provides vehicle position estimates in the absence of GPS signal via automated processing of roadway fiducials (primarily directional road signs). Sign images are detected and extracted from vehicle-mounted camera system, and preprocessed and read via a custom optical character recognition (OCR) system specifically designed to cope with low quality input imagery. Vehicle motion and 3D scene geometry estimation enables efficient and robust sign detection with low false alarm rates. Multi-level text processing coupled with GIS database validation enables effective interpretation even of extremely low resolution low contrast sign images. In this paper, ESARR development progress will be reported on, including the design and architecture, image processing framework, localization methodologies, and results to date. Highlights of the real-time vehicle-based directional road-sign detection and interpretation system will be described along with the challenges and progress in overcoming them.

Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition.

PubMed

Bianne-Bernard, Anne-Laure; Menasri, Farès; Al-Hajj Mohamad, Rami; Mokbel, Chafic; Kermorvant, Christopher; Likforman-Sulem, Laurence

2011-10-01

This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. Decision trees are built according to a set of expert-based questions on how characters are written. Questions are divided into global questions, yielding larger clusters, and precise questions, yielding smaller ones. Such clustering enables us to reduce the total number of models and Gaussians densities by 10. We then apply this modeling to the recognition of handwritten words. Experiments are conducted on three publicly available databases based on Latin or Arabic languages: Rimes, IAM, and OpenHart. The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition.

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.

Using Computer Technology To Monitor Student Progress and Remediate Reading Problems.

ERIC Educational Resources Information Center

McCullough, C. Sue

1995-01-01

Focuses on research about application of text-to-speech systems in diagnosing and remediating word recognition, vocabulary knowledge, and comprehension disabilities. As school psychologists move toward a consultative model of service delivery, they need to know about technology such as speech synthesizers, digitizers, optical-character-recognition…

TELLTALE: Experiments in a Dynamic Hypertext Environment for Degraded and Multilingual Data.

ERIC Educational Resources Information Center

Pearce, Claudia; Nicholas, Charles

1996-01-01

Presents experimentation results for the TELLTALE system, a dynamic hypertext environment that provides full-text search from a hypertext-style user interface for text corpora that may be garbled by OCR (optical character recognition) or transmission errors, and that may contain languages other than English. (Author/LRW)

U.S. Army Research Laboratory (ARL) Corporate Dari Document Transcription and Translation Guidelines

DTIC Science & Technology

2012-10-01

text file format. 15. SUBJECT TERMS Transcription, Translation, guidelines, ground truth, Optical character recognition , OCR, Machine Translation, MT...foreign language into a target language in order to train, test, and evaluate optical character recognition (OCR) and machine translation (MT) embedded...graphic element and should not be transcribed. Elements that are not part of the primary text such as handwritten annotations or stamps should not be

A method of neighbor classes based SVM classification for optical printed Chinese character recognition.

PubMed

Zhang, Jie; Wu, Xiaohong; Yu, Yanmei; Luo, Daisheng

2013-01-01

In optical printed Chinese character recognition (OPCCR), many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM) might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM) to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR.

Heuristic algorithm for optical character recognition of Arabic script

NASA Astrophysics Data System (ADS)

Yarman-Vural, Fatos T.; Atici, A.

1996-02-01

In this paper, a heuristic method is developed for segmentation, feature extraction and recognition of the Arabic script. The study is part of a large project for the transcription of the documents in Ottoman Archives. A geometrical and topological feature analysis method is developed for segmentation and feature extraction stages. Chain code transformation is applied to main strokes of the characters which are then classified by the hidden Markov model (HMM) in the recognition stage. Experimental results indicate that the performance of the proposed method is impressive, provided that the thinning process does not yield spurious branches.

Handwritten character recognition using background analysis

NASA Astrophysics Data System (ADS)

Tascini, Guido; Puliti, Paolo; Zingaretti, Primo

1993-04-01

The paper describes a low-cost handwritten character recognizer. It is constituted by three modules: the `acquisition' module, the `binarization' module, and the `core' module. The core module can be logically partitioned into six steps: character dilation, character circumscription, region and `profile' analysis, `cut' analysis, decision tree descent, and result validation. Firstly, it reduces the resolution of the binarized regions and detects the minimum rectangle (MR) which encloses the character; the MR partitions the background into regions that surround the character or are enclosed by it, and allows it to define features as `profiles' and `cuts;' a `profile' is the set of vertical or horizontal minimum distances between a side of the MR and the character itself; a `cut' is a vertical or horizontal image segment delimited by the MR. Then, the core module classifies the character by descending along the decision tree on the basis of the analysis of regions around the character, in particular of the `profiles' and `cuts,' and without using context information. Finally, it recognizes the character or reactivates the core module by analyzing validation test results. The recognizer is largely insensible to character discontinuity and is able to detect Arabic numerals and English alphabet capital letters. The recognition rate of a 32 X 32 pixel character is of about 97% after the first iteration, and of over 98% after the second iteration.

Quantitative computed tomography (QCT) as a radiology reporting tool by using optical character recognition (OCR) and macro program.

PubMed

Lee, Young Han; Song, Ho-Taek; Suh, Jin-Suck

2012-12-01

The objectives are (1) to introduce a new concept of making a quantitative computed tomography (QCT) reporting system by using optical character recognition (OCR) and macro program and (2) to illustrate the practical usages of the QCT reporting system in radiology reading environment. This reporting system was created as a development tool by using an open-source OCR software and an open-source macro program. The main module was designed for OCR to report QCT images in radiology reading process. The principal processes are as follows: (1) to save a QCT report as a graphic file, (2) to recognize the characters from an image as a text, (3) to extract the T scores from the text, (4) to perform error correction, (5) to reformat the values into QCT radiology reporting template, and (6) to paste the reports into the electronic medical record (EMR) or picture archiving and communicating system (PACS). The accuracy test of OCR was performed on randomly selected QCTs. QCT as a radiology reporting tool successfully acted as OCR of QCT. The diagnosis of normal, osteopenia, or osteoporosis is also determined. Error correction of OCR is done with AutoHotkey-coded module. The results of T scores of femoral neck and lumbar vertebrae had an accuracy of 100 and 95.4 %, respectively. A convenient QCT reporting system could be established by utilizing open-source OCR software and open-source macro program. This method can be easily adapted for other QCT applications and PACS/EMR.

Developing Multimedia Supplementary Materials to Support Learning Beginning Level Chinese Characters

ERIC Educational Resources Information Center

Xu, Lisha

2017-01-01

Studies investigating beginner Chinese learners' character learning strategies found that learners considered orthographic knowledge the most useful factor (Ke, 1998; Shen, 2005). Orthographic recognition correlates with character identification and production and can be used by advanced learners to solve word identification problems (Everson,…

A general framework for multicharacter segmentation and its application in recognizing multilingual Asian documents

NASA Astrophysics Data System (ADS)

Wen, Di; Ding, Xiaoqing

2003-12-01

In this paper we propose a general framework for character segmentation in complex multilingual documents, which is an endeavor to combine the traditionally separated segmentation and recognition processes into a cooperative system. The framework contains three basic steps: Dissection, Local Optimization and Global Optimization, which are designed to fuse various properties of the segmentation hypotheses hierarchically into a composite evaluation to decide the final recognition results. Experimental results show that this framework is general enough to be applied in variety of documents. A sample system based on this framework to recognize Chinese, Japanese and Korean documents and experimental performance is reported finally.

The effect of character contextual diversity on eye movements in Chinese sentence reading.

PubMed

Chen, Qingrong; Zhao, Guoxia; Huang, Xin; Yang, Yiming; Tanenhaus, Michael K

2017-12-01

Chen, Huang, et al. (Psychonomic Bulletin & Review, 2017) found that when reading two-character Chinese words embedded in sentence contexts, contextual diversity (CD), a measure of the proportion of texts in which a word appears, affected fixation times to words. When CD is controlled, however, frequency did not affect reading times. Two experiments used the same experimental designs to examine whether there are frequency effects of the first character of two-character words when CD is controlled. In Experiment 1, yoked triples of characters from a control group, a group matched for character CD that is lower in frequency, and a group matched in frequency with the control group, but higher in character CD, were rotated through the same sentence frame. In Experiment 2 each character from a larger set was embedded in a separate sentence frame, allowing for a larger difference in log frequency compared to Experiment 1 (0.8 and 0.4, respectively). In both experiments, early and later eye movement measures were significantly shorter for characters with higher CD than for characters with lower CD, with no effects of character frequency. These results place constraints on models of visual word recognition and suggest ways in which Chinese can be used to tease apart the nature of context effects in word recognition and language processing in general.

Segmental Rescoring in Text Recognition

DTIC Science & Technology

2014-02-04

description relates to rescoring text hypotheses in text recognition based on segmental features. Offline printed text and handwriting recognition (OHR) can... Handwriting , College Park, Md., 2006, which is incorporated by reference here. For the set of training images 202, a character modeler 208 receives

Character displacement of Cercopithecini primate visual signals

PubMed Central

Allen, William L.; Stevens, Martin; Higham, James P.

2014-01-01

Animal visual signals have the potential to act as an isolating barrier to prevent interbreeding of populations through a role in species recognition. Within communities of competing species, species recognition signals are predicted to undergo character displacement, becoming more visually distinctive from each other, however this pattern has rarely been identified. Using computational face recognition algorithms to model primate face processing, we demonstrate that the face patterns of guenons (tribe: Cercopithecini) have evolved under selection to become more visually distinctive from those of other guenon species with whom they are sympatric. The relationship between the appearances of sympatric species suggests that distinguishing conspecifics from other guenon species has been a major driver of diversification in guenon face appearance. Visual signals that have undergone character displacement may have had an important role in the tribe’s radiation, keeping populations that became geographically separated reproductively isolated on secondary contact. PMID:24967517

Template protection and its implementation in 3D face recognition systems

NASA Astrophysics Data System (ADS)

Zhou, Xuebing

2007-04-01

As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

Study of style effects on OCR errors in the MEDLINE database

NASA Astrophysics Data System (ADS)

Garrison, Penny; Davis, Diane L.; Andersen, Tim L.; Barney Smith, Elisa H.

2005-01-01

The National Library of Medicine has developed a system for the automatic extraction of data from scanned journal articles to populate the MEDLINE database. Although the 5-engine OCR system used in this process exhibits good performance overall, it does make errors in character recognition that must be corrected in order for the process to achieve the requisite accuracy. The correction process works by feeding words that have characters with less than 100% confidence (as determined automatically by the OCR engine) to a human operator who then must manually verify the word or correct the error. The majority of these errors are contained in the affiliation information zone where the characters are in italics or small fonts. Therefore only affiliation information data is used in this research. This paper examines the correlation between OCR errors and various character attributes in the MEDLINE database, such as font size, italics, bold, etc. and OCR confidence levels. The motivation for this research is that if a correlation between the character style and types of errors exists it should be possible to use this information to improve operator productivity by increasing the probability that the correct word option is presented to the human editor. We have determined that this correlation exists, in particular for the case of characters with diacritics.

Keyless Entry: Building a Text Database Using OCR Technology.

ERIC Educational Resources Information Center

Grotophorst, Clyde W.

1989-01-01

Discusses the use of optical character recognition (OCR) technology to produce an ASCII text database. A tutorial on digital scanning and OCR is provided, and a systems integration project which used the Calera CDP-3000XF scanner and text retrieval software to construct a database of dissertations at George Mason University is described. (four…

A Method of Neighbor Classes Based SVM Classification for Optical Printed Chinese Character Recognition

PubMed Central

Zhang, Jie; Wu, Xiaohong; Yu, Yanmei; Luo, Daisheng

2013-01-01

In optical printed Chinese character recognition (OPCCR), many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM) might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM) to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR. PMID:23536777

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.

The activation of segmental and tonal information in visual word recognition.

PubMed

Li, Chuchu; Lin, Candise Y; Wang, Min; Jiang, Nan

2013-08-01

Mandarin Chinese has a logographic script in which graphemes map onto syllables and morphemes. It is not clear whether Chinese readers activate phonological information during lexical access, although phonological information is not explicitly represented in Chinese orthography. In the present study, we examined the activation of phonological information, including segmental and tonal information in Chinese visual word recognition, using the Stroop paradigm. Native Mandarin speakers named the presentation color of Chinese characters in Mandarin. The visual stimuli were divided into five types: color characters (e.g., , hong2, "red"), homophones of the color characters (S+T+; e.g., , hong2, "flood"), different-tone homophones (S+T-; e.g., , hong1, "boom"), characters that shared the same tone but differed in segments with the color characters (S-T+; e.g., , ping2, "bottle"), and neutral characters (S-T-; e.g., , qian1, "leading through"). Classic Stroop facilitation was shown in all color-congruent trials, and interference was shown in the incongruent trials. Furthermore, the Stroop effect was stronger for S+T- than for S-T+ trials, and was similar between S+T+ and S+T- trials. These findings suggested that both tonal and segmental forms of information play roles in lexical constraints; however, segmental information has more weight than tonal information. We proposed a revised visual word recognition model in which the functions of both segmental and suprasegmental types of information and their relative weights are taken into account.

Benchmark for license plate character segmentation

NASA Astrophysics Data System (ADS)

Gonçalves, Gabriel Resende; da Silva, Sirlene Pio Gomes; Menotti, David; Shwartz, William Robson

2016-09-01

Automatic license plate recognition (ALPR) has been the focus of many researches in the past years. In general, ALPR is divided into the following problems: detection of on-track vehicles, license plate detection, segmentation of license plate characters, and optical character recognition (OCR). Even though commercial solutions are available for controlled acquisition conditions, e.g., the entrance of a parking lot, ALPR is still an open problem when dealing with data acquired from uncontrolled environments, such as roads and highways when relying only on imaging sensors. Due to the multiple orientations and scales of the license plates captured by the camera, a very challenging task of the ALPR is the license plate character segmentation (LPCS) step, because its effectiveness is required to be (near) optimal to achieve a high recognition rate by the OCR. To tackle the LPCS problem, this work proposes a benchmark composed of a dataset designed to focus specifically on the character segmentation step of the ALPR within an evaluation protocol. Furthermore, we propose the Jaccard-centroid coefficient, an evaluation measure more suitable than the Jaccard coefficient regarding the location of the bounding box within the ground-truth annotation. The dataset is composed of 2000 Brazilian license plates consisting of 14000 alphanumeric symbols and their corresponding bounding box annotations. We also present a straightforward approach to perform LPCS efficiently. Finally, we provide an experimental evaluation for the dataset based on five LPCS approaches and demonstrate the importance of character segmentation for achieving an accurate OCR.

The Effects of Graphic Similarity on Japanese Recognition of Simplified Chinese Characters

ERIC Educational Resources Information Center

Teng, Xiaochun; Yamada, Jun

2017-01-01

The pedagogical and theoretical questions addressed in this study relate to the extent to which native Japanese readers with little or no knowledge of Chinese characters recognize Chinese characters that are viewed as abbreviations of the kanji they already know. Three graphic similarity functions (i.e., an orthographically acceptable similarity,…

Interspecific aggression, not interspecific mating, drives character displacement in the wing coloration of male rubyspot damselflies (Hetaerina)

PubMed Central

Drury, J. P.; Grether, G. F.

2014-01-01

Traits that mediate intraspecific social interactions may overlap in closely related sympatric species, resulting in costly between-species interactions. Such interactions have principally interested investigators studying the evolution of reproductive isolation via reproductive character displacement (RCD) or reinforcement, yet in addition to reproductive interference, interspecific trait overlap can lead to costly between-species aggression. Previous research on rubyspot damselflies (Hetaerina spp.) demonstrated that sympatric shifts in male wing colour patterns and competitor recognition reduce interspecific aggression, supporting the hypothesis that agonistic character displacement (ACD) drove trait shifts. However, a recent theoretical model shows that RCD overshadows ACD if the same male trait is used for both female mate recognition and male competitor recognition. To determine whether female mate recognition is based on male wing coloration in Hetaerina, we conducted a phenotype manipulation experiment. Compared to control males, male H. americana with wings manipulated to resemble a sympatric congener (H. titia) suffered no reduction in mating success. Thus, female mate recognition is not based on species differences in male wing coloration. Experimental males did, however, experience higher interspecific fighting rates and reduced survival compared to controls. These results greatly strengthen the case for ACD and highlight the mechanistic distinction between ACD and RCD. PMID:25339724

Text vectorization based on character recognition and character stroke modeling

NASA Astrophysics Data System (ADS)

Fan, Zhigang; Zhou, Bingfeng; Tse, Francis; Mu, Yadong; He, Tao

2014-03-01

In this paper, a text vectorization method is proposed using OCR (Optical Character Recognition) and character stroke modeling. This is based on the observation that for a particular character, its font glyphs may have different shapes, but often share same stroke structures. Like many other methods, the proposed algorithm contains two procedures, dominant point determination and data fitting. The first one partitions the outlines into segments and second one fits a curve to each segment. In the proposed method, the dominant points are classified as "major" (specifying stroke structures) and "minor" (specifying serif shapes). A set of rules (parameters) are determined offline specifying for each character the number of major and minor dominant points and for each dominant point the detection and fitting parameters (projection directions, boundary conditions and smoothness). For minor points, multiple sets of parameters could be used for different fonts. During operation, OCR is performed and the parameters associated with the recognized character are selected. Both major and minor dominant points are detected as a maximization process as specified by the parameter set. For minor points, an additional step could be performed to test the competing hypothesis and detect degenerated cases.

Human-Computer Interface Controlled by Horizontal Directional Eye Movements and Voluntary Blinks Using AC EOG Signals

NASA Astrophysics Data System (ADS)

Kajiwara, Yusuke; Murata, Hiroaki; Kimura, Haruhiko; Abe, Koji

As a communication support tool for cases of amyotrophic lateral sclerosis (ALS), researches on eye gaze human-computer interfaces have been active. However, since voluntary and involuntary eye movements cannot be distinguished in the interfaces, their performance is still not sufficient for practical use. This paper presents a high performance human-computer interface system which unites high quality recognitions of horizontal directional eye movements and voluntary blinks. The experimental results have shown that the number of incorrect inputs is decreased by 35.1% in an existing system which equips recognitions of horizontal and vertical directional eye movements in addition to voluntary blinks and character inputs are speeded up by 17.4% from the existing system.

Integrative Lifecourse and Genetic Analysis of Military Working Dogs

DTIC Science & Technology

2012-10-01

Recognition), ICR (Intelligent Character Recognition) and HWR ( Handwriting Recognition). A number of various software packages were evaluated and we have...the third-party software is able to recognize check-boxes and columns and do a reasonable job with handwriting – which is does. This workflow will

Parsing and Tagging of Bilingual Dictionary

DTIC Science & Technology

2003-09-01

LAMP-TR-106 CAR-TR-991 CS-TR-4529 UMIACS-TR-2003-97 PARSING ANS TAGGING OF BILINGUAL DICTIONARY Huanfeng Ma1,2, Burcu Karagol-Ayan1,2, David... dictionaries hold great potential as a source of lexical resources for training and testing automated systems for optical character recognition, machine...translation, and cross-language information retrieval. In this paper, we describe a system for extracting term lexicons from printed bilingual dictionaries

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

Speech recognition for embedded automatic positioner for laparoscope

NASA Astrophysics Data System (ADS)

Chen, Xiaodong; Yin, Qingyun; Wang, Yi; Yu, Daoyin

2014-07-01

In this paper a novel speech recognition methodology based on Hidden Markov Model (HMM) is proposed for embedded Automatic Positioner for Laparoscope (APL), which includes a fixed point ARM processor as the core. The APL system is designed to assist the doctor in laparoscopic surgery, by implementing the specific doctor's vocal control to the laparoscope. Real-time respond to the voice commands asks for more efficient speech recognition algorithm for the APL. In order to reduce computation cost without significant loss in recognition accuracy, both arithmetic and algorithmic optimizations are applied in the method presented. First, depending on arithmetic optimizations most, a fixed point frontend for speech feature analysis is built according to the ARM processor's character. Then the fast likelihood computation algorithm is used to reduce computational complexity of the HMM-based recognition algorithm. The experimental results show that, the method shortens the recognition time within 0.5s, while the accuracy higher than 99%, demonstrating its ability to achieve real-time vocal control to the APL.

The Heinz Electronic Library Interactive Online System (HELIOS): Building a Digital Archive Using Imaging, OCR, and Natural Language Processing Technologies.

ERIC Educational Resources Information Center

Galloway, Edward A.; Michalek, Gabrielle V.

1995-01-01

Discusses the conversion project of the congressional papers of Senator John Heinz into digital format and the provision of electronic access to these papers by Carnegie Mellon University. Topics include collection background, project team structure, document processing, scanning, use of optical character recognition software, verification…

Planning the National Agricultural Library's Multimedia CD-ROM "Ornamental Horticulture."

ERIC Educational Resources Information Center

Mason, Pamela R.

1991-01-01

Discussion of issues involved in planning a multimedia CD-ROM product explains the selection of authoring tools, the design of a user interface, expert systems, text conversion and capture (including scanning and optical character recognition), and problems associated with image files. The use of audio is also discussed, and a 14-item glossary is…

Study of the Effectiveness of OCR for Decentralized Data Capture and Conversion. Final Report.

ERIC Educational Resources Information Center

Liston, David M.; And Others

The ERIC network conversion to an OCR (Optical Character Recognition) mode of data entry was studied to analyze the potential effectiveness of OCR data entry for future EPC/s (Editorial Processing Centers). Study results are also applicable to any other system involving decentralized bibliographic data capture and conversion functions. The report…

Using Singular Value Decomposition to Investigate Degraded Chinese Character Recognition: Evidence from Eye Movements during Reading

ERIC Educational Resources Information Center

Wang, Hsueh-Cheng; Schotter, Elizabeth R.; Angele, Bernhard; Yang, Jinmian; Simovici, Dan; Pomplun, Marc; Rayner, Keith

2013-01-01

Previous research indicates that removing initial strokes from Chinese characters makes them harder to read than removing final or internal ones. In the present study, we examined the contribution of important components to character configuration via singular value decomposition. The results indicated that when the least important segments, which…

Pattern recognition technique

NASA Technical Reports Server (NTRS)

Hong, J. P.

1971-01-01

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

Spatiotemporal Pixelization to Increase the Recognition Score of Characters for Retinal Prostheses

PubMed Central

Kim, Hyun Seok; Park, Kwang Suk

2017-01-01

Most of the retinal prostheses use a head-fixed camera and a video processing unit. Some studies proposed various image processing methods to improve visual perception for patients. However, previous studies only focused on using spatial information. The present study proposes a spatiotemporal pixelization method mimicking fixational eye movements to generate stimulation images for artificial retina arrays by combining spatial and temporal information. Input images were sampled with a resolution that was four times higher than the number of pixel arrays. We subsampled this image and generated four different phosphene images. We then evaluated the recognition scores of characters by sequentially presenting phosphene images with varying pixel array sizes (6 × 6, 8 × 8 and 10 × 10) and stimulus frame rates (10 Hz, 15 Hz, 20 Hz, 30 Hz, and 60 Hz). The proposed method showed the highest recognition score at a stimulus frame rate of approximately 20 Hz. The method also significantly improved the recognition score for complex characters. This method provides a new way to increase practical resolution over restricted spatial resolution by merging the higher resolution image into high-frame time slots. PMID:29073735

A survey of decision tree classifier methodology

NASA Technical Reports Server (NTRS)

Safavian, S. R.; Landgrebe, David

1991-01-01

Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

A survey of decision tree classifier methodology

NASA Technical Reports Server (NTRS)

Safavian, S. Rasoul; Landgrebe, David

1990-01-01

Decision Tree Classifiers (DTC's) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps, the most important feature of DTC's is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issue. After considering potential advantages of DTC's over single stage classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

reCAPTCHA: human-based character recognition via Web security measures.

PubMed

von Ahn, Luis; Maurer, Benjamin; McMillen, Colin; Abraham, David; Blum, Manuel

2008-09-12

CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) are widespread security measures on the World Wide Web that prevent automated programs from abusing online services. They do so by asking humans to perform a task that computers cannot yet perform, such as deciphering distorted characters. Our research explored whether such human effort can be channeled into a useful purpose: helping to digitize old printed material by asking users to decipher scanned words from books that computerized optical character recognition failed to recognize. We showed that this method can transcribe text with a word accuracy exceeding 99%, matching the guarantee of professional human transcribers. Our apparatus is deployed in more than 40,000 Web sites and has transcribed over 440 million words.

Sublexical Processing in Visual Recognition of Chinese Characters: Evidence from Repetition Blindness for Subcharacter Components

ERIC Educational Resources Information Center

Yeh, Su-Ling; Li, Jing-Ling

2004-01-01

Repetition blindness (RB) refers to the failure to detect the second occurrence of a repeated item in rapid serial visual presentation (RSVP). In two experiments using RSVP, the ability to report two critical characters was found to be impaired when these two characters were identical (Experiment 1) or similar by sharing one repeated component…

Recognition is Used as One Cue Among Others in Judgment and Decision Making

ERIC Educational Resources Information Center

Richter, Tobias; Spath, Pamela

2006-01-01

Three experiments with paired comparisons were conducted to test the noncompensatory character of the recognition heuristic (D. G. Goldstein & G. Gigerenzer, 2002) in judgment and decision making. Recognition and knowledge about the recognized alternative were manipulated. In Experiment 1, participants were presented pairs of animal names where…

Field programmable gate arrays-based number plate binarization and adjustment for automatic number plate recognition systems

NASA Astrophysics Data System (ADS)

Zhai, Xiaojun; Bensaali, Faycal; Sotudeh, Reza

2013-01-01

Number plate (NP) binarization and adjustment are important preprocessing stages in automatic number plate recognition (ANPR) systems and are used to link the number plate localization (NPL) and character segmentation stages. Successfully linking these two stages will improve the performance of the entire ANPR system. We present two optimized low-complexity NP binarization and adjustment algorithms. Efficient area/speed architectures based on the proposed algorithms are also presented and have been successfully implemented and tested using the Mentor Graphics RC240 FPGA development board, which together require only 9% of the available on-chip resources of a Virtex-4 FPGA, run with a maximum frequency of 95.8 MHz and are capable of processing one image in 0.07 to 0.17 ms.

Recognition of degraded handwritten digits using dynamic Bayesian networks

NASA Astrophysics Data System (ADS)

Likforman-Sulem, Laurence; Sigelle, Marc

2007-01-01

We investigate in this paper the application of dynamic Bayesian networks (DBNs) to the recognition of handwritten digits. The main idea is to couple two separate HMMs into various architectures. First, a vertical HMM and a horizontal HMM are built observing the evolving streams of image columns and image rows respectively. Then, two coupled architectures are proposed to model interactions between these two streams and to capture the 2D nature of character images. Experiments performed on the MNIST handwritten digit database show that coupled architectures yield better recognition performances than non-coupled ones. Additional experiments conducted on artificially degraded (broken) characters demonstrate that coupled architectures better cope with such degradation than non coupled ones and than discriminative methods such as SVMs.

Remembering the orientation of newly learned characters depends on the associated writing knowledge: a comparison between handwriting and typing.

PubMed

Longcamp, Marieke; Boucard, Céline; Gilhodes, Jean-Claude; Velay, Jean-Luc

2006-10-01

Recent data support the idea that movements play a crucial role in letter representation and suggest that handwriting knowledge contributes to visual recognition of letters. If so, using different motor activities while subjects are learning to write should affect their subsequent recognition performances. In order to test this hypothesis, we trained adult participants to write new characters either by copying them or by typing them on a keyboard. After three weeks of training we ran a series of tests requiring visual processing of the characters' orientation. Tests were ran immediately, one week after, and three weeks after the end of the training period. Results showed that when the characters had been learned by typing, they were more frequently confused with their mirror images than when they had been written by hand. This handwriting advantage did not appear immediately, but mostly three weeks after the end of the training. Our results therefore suggest that the stability of the characters' representation in memory depends on the nature of the motor activity produced during learning.

Artificial neural networks for document analysis and recognition.

PubMed

Marinai, Simone; Gori, Marco; Soda, Giovanni; Society, Computer

2005-01-01

Artificial neural networks have been extensively applied to document analysis and recognition. Most efforts have been devoted to the recognition of isolated handwritten and printed characters with widely recognized successful results. However, many other document processing tasks, like preprocessing, layout analysis, character segmentation, word recognition, and signature verification, have been effectively faced with very promising results. This paper surveys the most significant problems in the area of offline document image processing, where connectionist-based approaches have been applied. Similarities and differences between approaches belonging to different categories are discussed. A particular emphasis is given on the crucial role of prior knowledge for the conception of both appropriate architectures and learning algorithms. Finally, the paper provides a critical analysis on the reviewed approaches and depicts the most promising research guidelines in the field. In particular, a second generation of connectionist-based models are foreseen which are based on appropriate graphical representations of the learning environment.

Comparing the minimum spatial-frequency content for recognizing Chinese and alphabet characters

PubMed Central

Wang, Hui; Legge, Gordon E.

2018-01-01

Visual blur is a common problem that causes difficulty in pattern recognition for normally sighted people under degraded viewing conditions (e.g., near the acuity limit, when defocused, or in fog) and also for people with impaired vision. For reliable identification, the spatial frequency content of an object needs to extend up to or exceed a minimum value in units of cycles per object, referred to as the critical spatial frequency. In this study, we investigated the critical spatial frequency for alphabet and Chinese characters, and examined the effect of pattern complexity. The stimuli were divided into seven categories based on their perimetric complexity, including the lowercase and uppercase alphabet letters, and five groups of Chinese characters. We found that the critical spatial frequency significantly increased with complexity, from 1.01 cycles per character for the simplest group to 2.00 cycles per character for the most complex group of Chinese characters. A second goal of the study was to test a space-bandwidth invariance hypothesis that would represent a tradeoff between the critical spatial frequency and the number of adjacent patterns that can be recognized at one time. We tested this hypothesis by comparing the critical spatial frequencies in cycles per character from the current study and visual-span sizes in number of characters (measured by Wang, He, & Legge, 2014) for sets of characters with different complexities. For the character size (1.2°) we used in the study, we found an invariant product of approximately 10 cycles, which may represent a capacity limitation on visual pattern recognition. PMID:29297056

Neural Network--OCR/ICR Recognology: Theory and Applications.

ERIC Educational Resources Information Center

Schantz, Herbert F.

1993-01-01

Explains the value of neurocomputing as a unique and effective new technological concept for information processing and optical character recognition. Comparisons are made to digital computing and examples of applications such as recognizing handprinted characters are addressed. Products available from various companies are described. (Contains…

Effect of word familiarity on visually evoked magnetic fields.

PubMed

Harada, N; Iwaki, S; Nakagawa, S; Yamaguchi, M; Tonoike, M

2004-11-30

This study investigated the effect of word familiarity of visual stimuli on the word recognizing function of the human brain. Word familiarity is an index of the relative ease of word perception, and is characterized by facilitation and accuracy on word recognition. We studied the effect of word familiarity, using "Hiragana" (phonetic characters in Japanese orthography) characters as visual stimuli, on the elicitation of visually evoked magnetic fields with a word-naming task. The words were selected from a database of lexical properties of Japanese. The four "Hiragana" characters used were grouped and presented in 4 classes of degree of familiarity. The three components were observed in averaged waveforms of the root mean square (RMS) value on latencies at about 100 ms, 150 ms and 220 ms. The RMS value of the 220 ms component showed a significant positive correlation (F=(3/36); 5.501; p=0.035) with the value of familiarity. ECDs of the 220 ms component were observed in the intraparietal sulcus (IPS). Increments in the RMS value of the 220 ms component, which might reflect ideographical word recognition, retrieving "as a whole" were enhanced with increments of the value of familiarity. The interaction of characters, which increased with the value of familiarity, might function "as a large symbol"; and enhance a "pop-out" function with an escaping character inhibiting other characters and enhancing the segmentation of the character (as a figure) from the ground.

Transfer of the left-side bias effect in perceptual expertise: The case of simplified and traditional Chinese character recognition

PubMed Central

Liu, Tianyin; Yeh, Su-Ling

2018-01-01

The left-side bias (LSB) effect observed in face and expert Chinese character perception is suggested to be an expertise marker for visual object recognition. However, in character perception this effect is limited to characters printed in a familiar font (font-sensitive LSB effect). Here we investigated whether the LSB and font-sensitive LSB effects depend on participants’ familiarity with global structure or local component information of the stimuli through examining their transfer effects across simplified and traditional Chinese scripts: the two Chinese scripts share similar overall structures but differ in the visual complexity of local components in general. We found that LSB in expert Chinese character processing could be transferred to the Chinese script that the readers are unfamiliar with. In contrast, the font-sensitive LSB effect did not transfer, and was limited to characters with the visual complexity the readers were most familiar with. These effects suggest that the LSB effect may be generalized to another visual category with similar overall structures; in contrast, effects of within-category variations such as fonts may depend on familiarity with local component information of the stimuli, and thus may be limited to the exemplars of the category that experts are typically exposed to. PMID:29608570

Signature Verification Based on Handwritten Text Recognition

NASA Astrophysics Data System (ADS)

Viriri, Serestina; Tapamo, Jules-R.

Signatures continue to be an important biometric trait because it remains widely used primarily for authenticating the identity of human beings. This paper presents an efficient text-based directional signature recognition algorithm which verifies signatures, even when they are composed of special unconstrained cursive characters which are superimposed and embellished. This algorithm extends the character-based signature verification technique. The experiments carried out on the GPDS signature database and an additional database created from signatures captured using the ePadInk tablet, show that the approach is effective and efficient, with a positive verification rate of 94.95%.

Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1992-01-01

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

Reading Machines for Blind People.

ERIC Educational Resources Information Center

Fender, Derek H.

1983-01-01

Ten stages of developing reading machines for blind people are analyzed: handling of text material; optics; electro-optics; pattern recognition; character recognition; storage; speech synthesizers; browsing and place finding; computer indexing; and other sources of input. Cost considerations of the final product are emphasized. (CL)

Partitioning of the degradation space for OCR training

NASA Astrophysics Data System (ADS)

Barney Smith, Elisa H.; Andersen, Tim

2006-01-01

Generally speaking optical character recognition algorithms tend to perform better when presented with homogeneous data. This paper studies a method that is designed to increase the homogeneity of training data, based on an understanding of the types of degradations that occur during the printing and scanning process, and how these degradations affect the homogeneity of the data. While it has been shown that dividing the degradation space by edge spread improves recognition accuracy over dividing the degradation space by threshold or point spread function width alone, the challenge is in deciding how many partitions and at what value of edge spread the divisions should be made. Clustering of different types of character features, fonts, sizes, resolutions and noise levels shows that edge spread is indeed shown to be a strong indicator of the homogeneity of character data clusters.

Effects on Learning Logographic Character Formation in Computer-Assisted Handwriting Instruction

ERIC Educational Resources Information Center

Tsai, Chen-hui; Kuo, Chin-Hwa; Horng, Wen-Bing; Chen, Chun-Wen

2012-01-01

This paper reports on a study that investigates how different learning methods might affect the learning process of character handwriting among beginning college learners of Chinese, as measured by tests of recognition, approximate production, precise production, and awareness of conventional stroke sequence. Two methodologies were examined during…

The Inversion Effect for Chinese Characters Is Modulated by Radical Organization

ERIC Educational Resources Information Center

Luo, Canhuang; Chen, Wei; Zhang, Ye

2017-01-01

In studies of visual object recognition, strong inversion effects accompany the acquisition of expertise and imply the involvement of configural processing. Chinese literacy results in sensitivity to the orthography of Chinese characters. While there is some evidence that this orthographic sensitivity results in an inversion effect, and thus…

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.

Integrated segmentation and recognition of connected Ottoman script

NASA Astrophysics Data System (ADS)

Yalniz, Ismet Zeki; Altingovde, Ismail Sengor; Güdükbay, Uğur; Ulusoy, Özgür

2009-11-01

We propose a novel context-sensitive segmentation and recognition method for connected letters in Ottoman script. This method first extracts a set of segments from a connected script and determines the candidate letters to which extracted segments are most similar. Next, a function is defined for scoring each different syntactically correct sequence of these candidate letters. To find the candidate letter sequence that maximizes the score function, a directed acyclic graph is constructed. The letters are finally recognized by computing the longest path in this graph. Experiments using a collection of printed Ottoman documents reveal that the proposed method provides >90% precision and recall figures in terms of character recognition. In a further set of experiments, we also demonstrate that the framework can be used as a building block for an information retrieval system for digital Ottoman archives.

A paper form processing system with an error correcting function for reading handwritten Kanji strings

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

Katsumi Marukawa; Kazuki Nakashima; Masashi Koga

1994-12-31

This paper presents a paper form processing system with an error correcting function for reading handwritten kanji strings. In the paper form processing system, names and addresses are important key data, and especially this paper takes up an error correcting method for name and address recognition. The method automatically corrects errors of the kanji OCR (Optical Character Reader) with the help of word dictionaries and other knowledge. Moreover, it allows names and addresses to be written in any style. The method consists of word matching {open_quotes}furigana{close_quotes} verification for name strings, and address approval for address strings. For word matching, kanjimore » name candidates are extracted by automaton-type word matching. In {open_quotes}furigana{close_quotes} verification, kana candidate characters recognized by the kana OCR are compared with kana`s searched from the name dictionary based on kanji name candidates, given by the word matching. The correct name is selected from the results of word matching and furigana verification. Also, the address approval efficiently searches for the right address based on a bottom-up procedure which follows hierarchical relations from a lower placename to a upper one by using the positional condition among the placenames. We ascertained that the error correcting method substantially improves the recognition rate and processing speed in experiments on 5,032 forms.« less

Processing Of Binary Images

NASA Astrophysics Data System (ADS)

Hou, H. S.

1985-07-01

An overview of the recent progress in the area of digital processing of binary images in the context of document processing is presented here. The topics covered include input scan, adaptive thresholding, halftoning, scaling and resolution conversion, data compression, character recognition, electronic mail, digital typography, and output scan. Emphasis has been placed on illustrating the basic principles rather than descriptions of a particular system. Recent technology advances and research in this field are also mentioned.

Development of a Leader Training Model and System

DTIC Science & Technology

1980-01-01

recognition--are (a) the free - play , two-sided engagement which incorporates the crucial elements of complexity and uncertainty, (b) objective and real-time...changing conditions, many created by opposition action. In such a dynamic free - play environ- ment, further complicated by the confounding conditions...the ISD model with its emphasis on task analysis was considered less than adequate for the combat arms. The free - play character of the combat setting

BanglaLekha-Isolated: A multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters.

PubMed

Biswas, Mithun; Islam, Rafiqul; Shom, Gautam Kumar; Shopon, Md; Mohammed, Nabeel; Momen, Sifat; Abedin, Anowarul

2017-06-01

BanglaLekha-Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre-processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https://data.mendeley.com/datasets/hf6sf8zrkc/2.

Integrative Lifecourse and Genetic Analysis of Military Working Dogs

DTIC Science & Technology

2012-10-01

Intelligent Character Recognition) and HWR ( Handwriting Recognition). A number of various software packages were evaluated and we have settled on a...third-party software is able to recognize check-boxes and columns and do a reasonable job with handwriting – which is does. This workflow will

76 FR 39757 - Filing Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-06

... an optical character recognition process, such a document may contain recognition errors. CAUTION... network speed e-filing of these documents may be difficult. Pursuant to section II(C) above, the Secretary... optical scan format or a typed ``electronic signature,'' e.g., ``/s/Jane Doe.'' (3) In the case of a...

Machine-printed Arabic OCR

NASA Astrophysics Data System (ADS)

Hassibi, Khosrow M.

1994-02-01

This paper presents a brief overview of our research in the development of an OCR system for recognition of machine-printed texts in languages that use the Arabic alphabet. The cursive nature of machine-printed Arabic makes the segmentation of words into letters a challenging problem. In our approach, through a novel preliminary segmentation technique, a word is broken into pieces where each piece may not represent a valid letter in general. Neural networks trained on a training sample set of about 500 Arabic text images are used for recognition of these pieces. The rules governing the alphabet and character-level contextual information are used for recombining these pieces into valid letters. Higher-level contextual analysis schemes including the use of an Arabic lexicon and n-grams is also under development and are expected to improve the word recognition accuracy. The segmentation, recognition, and contextual analysis processes are closely integrated using a feedback scheme. The details of preparation of the training set and some recent results on training of the networks will be presented.

Why Learning to Write Chinese Is a Waste of Time: A Modest Proposal

ERIC Educational Resources Information Center

Allen, Joseph R.

2008-01-01

This article argues that for students of Chinese and Japanese, learning to write Chinese characters ("hanzi/kanji") by hand from memory is an inefficient use of resources. Rather, beginning students should focus on character/word recognition (reading) and electronic writing. Although electronic technologies have diminished the usefulness of…

The Role of Orthographic Neighborhood Size Effects in Chinese Word Recognition

ERIC Educational Resources Information Center

Li, Meng-Feng; Lin, Wei-Chun; Chou, Tai-Li; Yang, Fu-Ling; Wu, Jei-Tun

2015-01-01

Previous studies about the orthographic neighborhood size (NS) in Chinese have overlooked the morphological processing, and the co-variation between the character frequency and the the NS. The present study manipulated the word frequency and the NS simultaneously, with the leading character frequency controlled, to explore their influences on word…

Chinese Characters Elicit Face-Like N170 Inversion Effects

ERIC Educational Resources Information Center

Wang, Man-Ying; Kuo, Bo-Cheng; Cheng, Shih-Kuen

2011-01-01

Recognition of both faces and Chinese characters is commonly believed to rely on configural information. While faces typically exhibit behavioral and N170 inversion effects that differ from non-face stimuli (Rossion, Joyce, Cottrell, & Tarr, 2003), the current study examined whether a similar reliance on configural processing may result in similar…

Optical Mapping of Brain Activation and Connectivity in Occipitotemporal Cortex During Chinese Character Recognition.

PubMed

Hu, Zhishan; Zhang, Juan; Couto, Tania Alexandra; Xu, Shiyang; Luan, Ping; Yuan, Zhen

2018-06-22

In this study, functional near-infrared spectroscopy (fNIRS) was used to examine the brain activation and connectivity in occipitotemporal cortex during Chinese character recognition (CCR). Eighteen healthy participants were recruited to perform a well-designed task with three categories of stimuli (real characters, pseudo characters, and checkerboards). By inspecting the brain activation difference and its relationship with behavioral data, the left laterality during CCR was clearly identified in the Brodmann area (BA) 18 and 19. In addition, our novel findings also demonstrated that the bilateral superior temporal gyrus (STG), bilateral BA 19, and left fusiform gyrus were also involved in high-level lexical information processing such as semantic and phonological ones. Meanwhile, by examining functional brain networks, we discovered that the right BA 19 exhibited enhanced brain connectivity. In particular, the connectivity in the right fusiform gyrus, right BA 19, and left STG showed significant correlation with the performance of CCR. Consequently, the combination of fNIRS technique with functional network analysis paves a new avenue for improved understanding of the cognitive mechanism underlying CCR.

A DDC Bibliography on Optical or Graphic Information Processing (Information Sciences Series). Volume I.

ERIC Educational Resources Information Center

Defense Documentation Center, Alexandria, VA.

This unclassified-unlimited bibliography contains 183 references, with abstracts, dealing specifically with optical or graphic information processing. Citations are grouped under three headings: display devices and theory, character recognition, and pattern recognition. Within each group, they are arranged in accession number (AD-number) sequence.…

Giro form reading machine

NASA Astrophysics Data System (ADS)

Minh Ha, Thien; Niggeler, Dieter; Bunke, Horst; Clarinval, Jose

1995-08-01

Although giro forms are used by many people in daily life for money remittance in Switzerland, the processing of these forms at banks and post offices is only partly automated. We describe an ongoing project for building an automatic system that is able to recognize various items printed or written on a giro form. The system comprises three main components, namely, an automatic form feeder, a camera system, and a computer. These components are connected in such a way that the system is able to process a bunch of forms without any human interactions. We present two real applications of our system in the field of payment services, which require the reading of both machine printed and handwritten information that may appear on a giro form. One particular feature of giro forms is their flexible layout, i.e., information items are located differently from one form to another, thus requiring an additional analysis step to localize them before recognition. A commercial optical character recognition software package is used for recognition of machine-printed information, whereas handwritten information is read by our own algorithms, the details of which are presented. The system is implemented by using a client/server architecture providing a high degree of flexibility to change. Preliminary results are reported supporting our claim that the system is usable in practice.

BACS: The Brussels Artificial Character Sets for studies in cognitive psychology and neuroscience.

PubMed

Vidal, Camille; Content, Alain; Chetail, Fabienne

2017-12-01

Written symbols such as letters have been used extensively in cognitive psychology, whether to understand their contributions to written word recognition or to examine the processes involved in other mental functions. Sometimes, however, researchers want to manipulate letters while removing their associated characteristics. A powerful solution to do so is to use new characters, devised to be highly similar to letters, but without the associated sound or name. Given the growing use of artificial characters in experimental paradigms, the aim of the present study was to make available the Brussels Artificial Character Sets (BACS): two full, strictly controlled, and portable sets of artificial characters for a broad range of experimental situations.

Adversity, emotion recognition, and empathic concern in high-risk youth.

PubMed

Quas, Jodi A; Dickerson, Kelli L; Matthew, Richard; Harron, Connor; Quas, Catherine M

2017-01-01

Little is known about how emotion recognition and empathy jointly operate in youth growing up in contexts defined by persistent adversity. We investigated whether adversity exposure in two groups of youth was associated with reduced empathy and whether deficits in emotion recognition mediated this association. Foster, rural poor, and comparison youth from Swaziland, Africa identified emotional expressions and rated their empathic concern for characters depicted in images showing positive, ambiguous, and negative scenes. Rural and foster youth perceived greater anger and happiness in the main characters in ambiguous and negative images than did comparison youth. Rural children also perceived less sadness. Youth's perceptions of sadness in the negative and ambiguous expressions mediated the relation between adversity and empathic concern, but only for the rural youth, who perceived less sadness, which then predicted less empathy. Findings provide new insight into processes that underlie empathic tendencies in adversity-exposed youth and highlight potential directions for interventions to increase empathy.

Combining convolutional neural networks and Hough Transform for classification of images containing lines

NASA Astrophysics Data System (ADS)

Sheshkus, Alexander; Limonova, Elena; Nikolaev, Dmitry; Krivtsov, Valeriy

2017-03-01

In this paper, we propose an expansion of convolutional neural network (CNN) input features based on Hough Transform. We perform morphological contrasting of source image followed by Hough Transform, and then use it as input for some convolutional filters. Thus, CNNs computational complexity and the number of units are not affected. Morphological contrasting and Hough Transform are the only additional computational expenses of introduced CNN input features expansion. Proposed approach was demonstrated on the example of CNN with very simple structure. We considered two image recognition problems, that were object classification on CIFAR-10 and printed character recognition on private dataset with symbols taken from Russian passports. Our approach allowed to reach noticeable accuracy improvement without taking much computational effort, which can be extremely important in industrial recognition systems or difficult problems utilising CNNs, like pressure ridge analysis and classification.

Enhancement Of Reading Accuracy By Multiple Data Integration

NASA Astrophysics Data System (ADS)

Lee, Kangsuk

1989-07-01

In this paper, a multiple sensor integration technique with neural network learning algorithms is presented which can enhance the reading accuracy of the hand-written numerals. Many document reading applications involve hand-written numerals in a predetermined location on a form, and in many cases, critical data is redundantly described. The amount of a personal check is one such case which is written redundantly in numerals and in alphabetical form. Information from two optical character recognition modules, one specialized for digits and one for words, is combined to yield an enhanced recognition of the amount. The combination can be accomplished by a decision tree with "if-then" rules, but by simply fusing two or more sets of sensor data in a single expanded neural net, the same functionality can be expected with a much reduced system cost. Experimental results of fusing two neural nets to enhance overall recognition performance using a controlled data set are presented.

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

[The present state and progress of researches on gait recognition].

PubMed

Xue, Zhaojun; Jin, Jingna; Ming, Dong; Wan, Baikun

2008-10-01

Recognition by gait is a new field for the biometric recognition technology. Its aim is to recognize people and detect physiological, pathological and mental characters by their walk style. The use of gait as a biometric for human identification is promising. The technique of gait recognition, as an attractive research area of biomedical information detection, attracts more and more attention. In this paper is introduced a survey of the basic theory, existing gait recognition methods and potential prospects. The latest progress and key factors of research difficulties are analyzed, and future researches are envisaged.

Do Dyslexic Individuals Present a Reduced Visual Attention Span? Evidence from Visual Recognition Tasks of Non-Verbal Multi-Character Arrays

ERIC Educational Resources Information Center

Yeari, Menahem; Isser, Michal; Schiff, Rachel

2017-01-01

A controversy has recently developed regarding the hypothesis that developmental dyslexia may be caused, in some cases, by a reduced visual attention span (VAS). To examine this hypothesis, independent of phonological abilities, researchers tested the ability of dyslexic participants to recognize arrays of unfamiliar visual characters. Employing…

Invention and validation of an automated camera system that uses optical character recognition to identify patient name mislabeled samples.

PubMed

Hawker, Charles D; McCarthy, William; Cleveland, David; Messinger, Bonnie L

2014-03-01

Mislabeled samples are a serious problem in most clinical laboratories. Published error rates range from 0.39/1000 to as high as 1.12%. Standardization of bar codes and label formats has not yet achieved the needed improvement. The mislabel rate in our laboratory, although low compared with published rates, prompted us to seek a solution to achieve zero errors. To reduce or eliminate our mislabeled samples, we invented an automated device using 4 cameras to photograph the outside of a sample tube. The system uses optical character recognition (OCR) to look for discrepancies between the patient name in our laboratory information system (LIS) vs the patient name on the customer label. All discrepancies detected by the system's software then require human inspection. The system was installed on our automated track and validated with production samples. We obtained 1 009 830 images during the validation period, and every image was reviewed. OCR passed approximately 75% of the samples, and no mislabeled samples were passed. The 25% failed by the system included 121 samples actually mislabeled by patient name and 148 samples with spelling discrepancies between the patient name on the customer label and the patient name in our LIS. Only 71 of the 121 mislabeled samples detected by OCR were found through our normal quality assurance process. We have invented an automated camera system that uses OCR technology to identify potential mislabeled samples. We have validated this system using samples transported on our automated track. Full implementation of this technology offers the possibility of zero mislabeled samples in the preanalytic stage.

Translation lexicon acquisition from bilingual dictionaries

NASA Astrophysics Data System (ADS)

Doermann, David S.; Ma, Huanfeng; Karagol-Ayan, Burcu; Oard, Douglas W.

2001-12-01

Bilingual dictionaries hold great potential as a source of lexical resources for training automated systems for optical character recognition, machine translation and cross-language information retrieval. In this work we describe a system for extracting term lexicons from printed copies of bilingual dictionaries. We describe our approach to page and definition segmentation and entry parsing. We have used the approach to parse a number of dictionaries and demonstrate the results for retrieval using a French-English Dictionary to generate a translation lexicon and a corpus of English queries applied to French documents to evaluation cross-language IR.

Neighborhood Frequency Effect in Chinese Word Recognition: Evidence from Naming and Lexical Decision

ERIC Educational Resources Information Center

Li, Meng-Feng; Gao, Xin-Yu; Chou, Tai-Li; Wu, Jei-Tun

2017-01-01

Neighborhood frequency is a crucial variable to know the nature of word recognition. Different from alphabetic scripts, neighborhood frequency in Chinese is usually confounded by component character frequency and neighborhood size. Three experiments were designed to explore the role of the neighborhood frequency effect in Chinese and the stimuli…

An Investigation of the Compensatory Effectiveness of Assistive Technology on Postsecondary Students with Learning Disabilities. Final Report.

ERIC Educational Resources Information Center

Murphy, Harry; Higgins, Eleanor

This final report describes the activities and accomplishments of a 3-year study on the compensatory effectiveness of three assistive technologies, optical character recognition, speech synthesis, and speech recognition, on postsecondary students (N=140) with learning disabilities. These technologies were investigated relative to: (1) immediate…

Is Syntactic-Category Processing Obligatory in Visual Word Recognition? Evidence from Chinese

ERIC Educational Resources Information Center

Wong, Andus Wing-Kuen; Chen, Hsuan-Chih

2012-01-01

Three experiments were conducted to investigate how syntactic-category and semantic information is processed in visual word recognition. The stimuli were two-character Chinese words in which semantic and syntactic-category ambiguities were factorially manipulated. A lexical decision task was employed in Experiment 1, whereas a semantic relatedness…

76 FR 64175 - Loans in Areas Having Special Flood Hazards; Interagency Questions and Answers Regarding Flood...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-17

... such as logos and special characters. Identifying information that you provide, such as phone numbers... are further made in recognition of the position, set out in the revisions to proposed question and...-day notice period. However, in recognition of standard provisions in many contracts entered into...

Offline handwritten word recognition using MQDF-HMMs

NASA Astrophysics Data System (ADS)

Ramachandrula, Sitaram; Hambarde, Mangesh; Patial, Ajay; Sahoo, Dushyant; Kochar, Shaivi

2015-01-01

We propose an improved HMM formulation for offline handwriting recognition (HWR). The main contribution of this work is using modified quadratic discriminant function (MQDF) [1] within HMM framework. In an MQDF-HMM the state observation likelihood is calculated by a weighted combination of MQDF likelihoods of individual Gaussians of GMM (Gaussian Mixture Model). The quadratic discriminant function (QDF) of a multivariate Gaussian can be rewritten by avoiding the inverse of covariance matrix by using the Eigen values and Eigen vectors of it. The MQDF is derived from QDF by substituting few of badly estimated lower-most Eigen values by an appropriate constant. The estimation errors of non-dominant Eigen vectors and Eigen values of covariance matrix for which the training data is insufficient can be controlled by this approach. MQDF has been successfully shown to improve the character recognition performance [1]. The usage of MQDF in HMM improves the computation, storage and modeling power of HMM when there is limited training data. We have got encouraging results on offline handwritten character (NIST database) and word recognition in English using MQDF HMMs.

Development of a written music-recognition system using Java and open source technologies

NASA Astrophysics Data System (ADS)

Loibner, Gernot; Schwarzl, Andreas; Kovač, Matthias; Paulus, Dietmar; Pölzleitner, Wolfgang

2005-10-01

We report on the development of a software system to recognize and interpret printed music. The overall goal is to scan printed music sheets, analyze and recognize the notes, timing, and written text, and derive the all necessary information to use the computers MIDI sound system to play the music. This function is primarily useful for musicians who want to digitize printed music for editing purposes. There exist a number of commercial systems that offer such a functionality. However, on testing these systems, we were astonished on how weak they behave in their pattern recognition parts. Although we submitted very clear and rather flawless scanning input, none of these systems was able to e.g. recognize all notes, staff lines, and systems. They all require a high degree of interaction, post-processing, and editing to get a decent digital version of the hard copy material. In this paper we focus on the pattern recognition area. In a first approach we tested more or less standard methods of adaptive thresholding, blob detection, line detection, and corner detection to find the notes, staff lines, and candidate objects subject to OCR. Many of the objects on this type of material can be learned in a training phase. None of the commercial systems we saw offers the option to train special characters or unusual signatures. A second goal in this project is to use a modern software engineering platform. We were interested in how well Java and open source technologies are suitable for pattern recognition and machine vision. The scanning of music served as a case-study.

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.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

NASA Astrophysics Data System (ADS)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

Differentiation of perceptual and semantic subsequent memory effects using an orthographic paradigm.

PubMed

Kuo, Michael C C; Liu, Karen P Y; Ting, Kin Hung; Chan, Chetwyn C H

2012-11-27

This study aimed to differentiate perceptual and semantic encoding processes using subsequent memory effects (SMEs) elicited by the recognition of orthographs of single Chinese characters. Participants studied a series of Chinese characters perceptually (by inspecting orthographic components) or semantically (by determining the object making sounds), and then made studied or unstudied judgments during the recognition phase. Recognition performance in terms of d-prime measure in the semantic condition was higher, though not significant, than that of the perceptual condition. The between perceptual-semantic condition differences in SMEs at P550 and late positive component latencies (700-1000ms) were not significant in the frontal area. An additional analysis identified larger SME in the semantic condition during 600-1000ms in the frontal pole regions. These results indicate that coordination and incorporation of orthographic information into mental representation is essential to both task conditions. The differentiation was also revealed in earlier SMEs (perceptual>semantic) at N3 (240-360ms) latency, which is a novel finding. The left-distributed N3 was interpreted as more efficient processing of meaning with semantically learned characters. Frontal pole SMEs indicated strategic processing by executive functions, which would further enhance memory. Copyright © 2012 Elsevier B.V. All rights reserved.

Program Descriptions for Interactive Signal and Pattern Analysis and Recognition System (ISPARS).

DTIC Science & Technology

1984-03-01

procedures for the ISPARS components developed at the David Taylor Naval Ship Reserach and Development Center (DTNSRDC), which are not documented in other...an alphabetic character. Some commands may consist of a letter and one or two two-digit numbers, separated by a space as specified in the table. 81 I-I... PAPERS INTENDED FOR IN- TERNAL USE. THEY CARRY AN IDENTIFYING NUMBER WHICH INDICATES THEIR TYPE AND THE NUMERICAL CODE OF THE ORIGINATING DEPARTMENT

Research on the optoacoustic communication system for speech transmission by variable laser-pulse repetition rates

NASA Astrophysics Data System (ADS)

Jiang, Hongyan; Qiu, Hongbing; He, Ning; Liao, Xin

2018-06-01

For the optoacoustic communication from in-air platforms to submerged apparatus, a method based on speech recognition and variable laser-pulse repetition rates is proposed, which realizes character encoding and transmission for speech. Firstly, the theories and spectrum characteristics of the laser-generated underwater sound are analyzed; and moreover character conversion and encoding for speech as well as the pattern of codes for laser modulation is studied; lastly experiments to verify the system design are carried out. Results show that the optoacoustic system, where laser modulation is controlled by speech-to-character baseband codes, is beneficial to improve flexibility in receiving location for underwater targets as well as real-time performance in information transmission. In the overwater transmitter, a pulse laser is controlled to radiate by speech signals with several repetition rates randomly selected in the range of one to fifty Hz, and then in the underwater receiver laser pulse repetition rate and data can be acquired by the preamble and information codes of the corresponding laser-generated sound. When the energy of the laser pulse is appropriate, real-time transmission for speaker-independent speech can be realized in that way, which solves the problem of underwater bandwidth resource and provides a technical approach for the air-sea communication.

Feature-extracted joint transform correlation.

PubMed

Alam, M S

1995-12-10

A new technique for real-time optical character recognition that uses a joint transform correlator is proposed. This technique employs feature-extracted patterns for the reference image to detect a wide range of characters in one step. The proposed technique significantly enhances the processing speed when compared with the presently available joint transform correlator architectures and shows feasibility for multichannel joint transform correlation.

Loose, Falling Characters and Sentences: The Persistence of the OCR Problem in Digital Repository E-Books

ERIC Educational Resources Information Center

Kichuk, Diana

2015-01-01

The electronic conversion of scanned image files to readable text using optical character recognition (OCR) software and the subsequent migration of raw OCR text to e-book text file formats are key remediation or media conversion technologies used in digital repository e-book production. Despite real progress, the OCR problem of reliability and…

Younger and Older Users’ Recognition of Virtual Agent Facial Expressions

PubMed Central

Beer, Jenay M.; Smarr, Cory-Ann; Fisk, Arthur D.; Rogers, Wendy A.

2015-01-01

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent’s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell, Sullivan, Prevost, & Churchill, 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck & Reichenbach, 2005; Courgeon et al. 2009; 2011; Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent’s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a possible explanation for age-related differences in emotion recognition. First, our findings show age-related differences in the recognition of emotions expressed by a virtual agent, with older adults showing lower recognition for the emotions of anger, disgust, fear, happiness, sadness, and neutral. These age-related difference might be explained by older adults having difficulty discriminating similarity in configural arrangement of facial features for certain emotions; for example, older adults often mislabeled the similar emotions of fear as surprise. Second, our results did not provide evidence for the dynamic formation improving emotion recognition; but, in general, the intensity of the emotion improved recognition. Lastly, we learned that emotion recognition, for older and younger adults, differed by character type, from best to worst: human, synthetic human, and then iCat. Our findings provide guidance for design, as well as the development of a framework of age-related differences in emotion recognition. PMID:25705105

Text recognition and correction for automated data collection by mobile devices

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-03-01

Participatory sensing is an approach which allows mobile devices such as mobile phones to be used for data collection, analysis and sharing processes by individuals. Data collection is the first and most important part of a participatory sensing system, but it is time consuming for the participants. In this paper, we discuss automatic data collection approaches for reducing the time required for collection, and increasing the amount of collected data. In this context, we explore automated text recognition on images of store receipts which are captured by mobile phone cameras, and the correction of the recognized text. Accordingly, our first goal is to evaluate the performance of the Optical Character Recognition (OCR) method with respect to data collection from store receipt images. Images captured by mobile phones exhibit some typical problems, and common image processing methods cannot handle some of them. Consequently, the second goal is to address these types of problems through our proposed Knowledge Based Correction (KBC) method used in support of the OCR, and also to evaluate the KBC method with respect to the improvement on the accurate recognition rate. Results of the experiments show that the KBC method improves the accurate data recognition rate noticeably.

Analog design of a new neural network for optical character recognition.

PubMed

Morns, I P; Dlay, S S

1999-01-01

An electronic circuit is presented for a new type of neural network, which gives a recognition rate of over 100 kHz. The network is used to classify handwritten numerals, presented as Fourier and wavelet descriptors, and has been shown to train far quicker than the popular backpropagation network while maintaining classification accuracy.

26 CFR 1.367(a)-6T - Transfer of foreign branch with previously deducted losses (temporary).

Code of Federal Regulations, 2011 CFR

2011-04-01

... the recognition of the gain realized on the transfer. Paragraph (c) of this section sets forth rules concerning the character of, and limitations on, the gain required to be recognized. Paragraph (d) of this... section. Finally, paragraph (g) of this section defines the term foreign branch. (b) Recognition of gain...

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Development of a Digitalized Child's Checkups Information System.

PubMed

Ito, Yoshiya; Takimoto, Hidemi

2017-01-01

In Japan, health checkups for children take place from infancy through high school and play an important role in the maintenance and control of childhood/adolescent health. The anthropometric data obtained during these checkups are kept in health centers and schools and are also recorded in a mother's maternal and child health handbook, as well as on school health cards. These data are meaningful if they are utilized well and in an appropriate manner. They are particularly useful for the prevention of obesity-related conditions in adulthood, such as metabolic syndrome and diabetes mellitus. For this purpose, we have tried to establish a scanning system with an optical character recognition (OCR) function, which links data obtained during health checkups in infancy with that obtained in schools. In this system, handwritten characters on the records are scanned and processed using OCR. However, because many of the scanned characters are not read properly, we must wait for the improvement in the performance of the OCR function. In addition, we have developed Microsoft Excel spreadsheets, on which obesity-related indices, such as body mass index and relative body weight, are calculated. These sheets also provide functions that tabulate the frequencies of obesity in specific groups. Actively using these data and digitalized systems will not only contribute towards resolving physical health problems in children, but also decrease the risk of developing lifestyle-related diseases in adulthood.

Enhancement and character recognition of the erased colophon of a 15th-century Hebrew prayer book

NASA Astrophysics Data System (ADS)

Walvoord, Derek J.; Easton, Roger L., Jr.; Knox, Keith T.; Heimbueger, Matthew

2005-01-01

A handwritten codex often included an inscription that listed facts about its publication, such as the names of the scribe and patron, date of publication, the city where the book was copied, etc. These facts obviously provide essential information to a historian studying the provenance of the codex. Unfortunately, this page was sometimes erased after the sale of the book to a new owner, often by scraping off the original ink. The importance of recovering this information would be difficult to overstate. This paper reports on the methods of imaging, image enhancement, and character recognition that were applied to this page in a Hebrew prayer book copied in Florence in the 15th century.

Enhancement and character recognition of the erased colophon of a 15th-century Hebrew prayer book

NASA Astrophysics Data System (ADS)

Walvoord, Derek J.; Easton, Roger L., Jr.; Knox, Keith T.; Heimbueger, Matthew

2004-12-01

A handwritten codex often included an inscription that listed facts about its publication, such as the names of the scribe and patron, date of publication, the city where the book was copied, etc. These facts obviously provide essential information to a historian studying the provenance of the codex. Unfortunately, this page was sometimes erased after the sale of the book to a new owner, often by scraping off the original ink. The importance of recovering this information would be difficult to overstate. This paper reports on the methods of imaging, image enhancement, and character recognition that were applied to this page in a Hebrew prayer book copied in Florence in the 15th century.

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.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

Adversity, emotion recognition, and empathic concern in high-risk youth

PubMed Central

Quas, Jodi A.; Matthew, Richard; Harron, Connor; Quas, Catherine M.

2017-01-01

Little is known about how emotion recognition and empathy jointly operate in youth growing up in contexts defined by persistent adversity. We investigated whether adversity exposure in two groups of youth was associated with reduced empathy and whether deficits in emotion recognition mediated this association. Foster, rural poor, and comparison youth from Swaziland, Africa identified emotional expressions and rated their empathic concern for characters depicted in images showing positive, ambiguous, and negative scenes. Rural and foster youth perceived greater anger and happiness in the main characters in ambiguous and negative images than did comparison youth. Rural children also perceived less sadness. Youth’s perceptions of sadness in the negative and ambiguous expressions mediated the relation between adversity and empathic concern, but only for the rural youth, who perceived less sadness, which then predicted less empathy. Findings provide new insight into processes that underlie empathic tendencies in adversity-exposed youth and highlight potential directions for interventions to increase empathy. PMID:28738074

A Dynamic Bayesian Network Based Structural Learning towards Automated Handwritten Digit Recognition

NASA Astrophysics Data System (ADS)

Pauplin, Olivier; Jiang, Jianmin

Pattern recognition using Dynamic Bayesian Networks (DBNs) is currently a growing area of study. In this paper, we present DBN models trained for classification of handwritten digit characters. The structure of these models is partly inferred from the training data of each class of digit before performing parameter learning. Classification results are presented for the four described models.

Neural basis of hierarchical visual form processing of Japanese Kanji characters.

PubMed

Higuchi, Hiroki; Moriguchi, Yoshiya; Murakami, Hiroki; Katsunuma, Ruri; Mishima, Kazuo; Uno, Akira

2015-12-01

We investigated the neural processing of reading Japanese Kanji characters, which involves unique hierarchical visual processing, including the recognition of visual components specific to Kanji, such as "radicals." We performed functional MRI to measure brain activity in response to hierarchical visual stimuli containing (1) real Kanji characters (complete structure with semantic information), (2) pseudo Kanji characters (subcomponents without complete character structure), (3) artificial characters (character fragments), and (4) checkerboard (simple photic stimuli). As we expected, the peaks of the activation in response to different stimulus types were aligned within the left occipitotemporal visual region along the posterior-anterior axis in order of the structural complexity of the stimuli, from fragments (3) to complete characters (1). Moreover, only the real Kanji characters produced functional connectivity between the left inferotemporal area and the language area (left inferior frontal triangularis), while pseudo Kanji characters induced connectivity between the left inferotemporal area and the bilateral cerebellum and left putamen. Visual processing of Japanese Kanji takes place in the left occipitotemporal cortex, with a clear hierarchy within the region such that the neural activation differentiates the elements in Kanji characters' fragments, subcomponents, and semantics, with different patterns of connectivity to remote regions among the elements.

Agonistic character displacement in social cognition of advertisement signals.

PubMed

Pasch, Bret; Sanford, Rachel; Phelps, Steven M

2017-03-01

Interspecific aggression between sibling species may enhance discrimination of competitors when recognition errors are costly, but proximate mechanisms mediating increased discriminative ability are unclear. We studied behavioral and neural mechanisms underlying responses to conspecific and heterospecific vocalizations in Alston's singing mouse (Scotinomys teguina), a species in which males sing to repel rivals. We performed playback experiments using males in allopatry and sympatry with a dominant heterospecific (Scotinomys xerampelinus) and examined song-evoked induction of egr-1 in the auditory system to examine how neural tuning modulates species-specific responses. Heterospecific songs elicited stronger neural responses in sympatry than in allopatry, despite eliciting less singing in sympatry. Our results refute the traditional neuroethological concept of a matched filter and instead suggest expansion of sensory sensitivity to mediate competitor recognition in sympatry.

Korean letter handwritten recognition using deep convolutional neural network on android platform

NASA Astrophysics Data System (ADS)

Purnamawati, S.; Rachmawati, D.; Lumanauw, G.; Rahmat, R. F.; Taqyuddin, R.

2018-03-01

Currently, popularity of Korean culture attracts many people to learn everything about Korea, particularly its language. To acquire Korean Language, every single learner needs to be able to understand Korean non-Latin character. A digital approach needs to be carried out in order to make Korean learning process easier. This study is done by using Deep Convolutional Neural Network (DCNN). DCNN performs the recognition process on the image based on the model that has been trained such as Inception-v3 Model. Subsequently, re-training process using transfer learning technique with the trained and re-trained value of model is carried though in order to develop a new model with a better performance without any specific systemic errors. The testing accuracy of this research results in 86,9%.

The location and recognition of anti-counterfeiting code image with complex background

NASA Astrophysics Data System (ADS)

Ni, Jing; Liu, Quan; Lou, Ping; Han, Ping

2017-07-01

The order of cigarette market is a key issue in the tobacco business system. The anti-counterfeiting code, as a kind of effective anti-counterfeiting technology, can identify counterfeit goods, and effectively maintain the normal order of market and consumers' rights and interests. There are complex backgrounds, light interference and other problems in the anti-counterfeiting code images obtained by the tobacco recognizer. To solve these problems, the paper proposes a locating method based on Susan operator, combined with sliding window and line scanning,. In order to reduce the interference of background and noise, we extract the red component of the image and convert the color image into gray image. For the confusing characters, recognition results correction based on the template matching method has been adopted to improve the recognition rate. In this method, the anti-counterfeiting code can be located and recognized correctly in the image with complex background. The experiment results show the effectiveness and feasibility of the approach.

When is the right hemisphere holistic and when is it not? The case of Chinese character recognition.

PubMed

Chung, Harry K S; Leung, Jacklyn C Y; Wong, Vienne M Y; Hsiao, Janet H

2018-05-15

Holistic processing (HP) has long been considered a characteristic of right hemisphere (RH) processing. Indeed, holistic face processing is typically associated with left visual field (LVF)/RH processing advantages. Nevertheless, expert Chinese character recognition involves reduced HP and increased RH lateralization, presenting a counterexample. Recent modeling research suggests that RH processing may be associated with an increase or decrease in HP, depending on whether spacing or component information was used respectively. Since expert Chinese character recognition involves increasing sensitivity to components while deemphasizing spacing information, RH processing in experts may be associated with weaker HP than novices. Consistent with this hypothesis, in a divided visual field paradigm, novices exhibited HP only in the LVF/RH, whereas experts showed no HP in either visual field. This result suggests that the RH may flexibly switch between part-based and holistic representations, consistent with recent fMRI findings. The RH's advantage in global/low spatial frequency processing is suggested to be relative to the task relevant frequency range. Thus, its use of holistic and part-based representations may depend on how attention is allocated for task relevant information. This study provides the first behavioral evidence showing how type of information used for processing modulates perceptual representations in the RH. Copyright © 2018 Elsevier B.V. All rights reserved.

Con-Text: Text Detection for Fine-grained Object Classification.

PubMed

Karaoglu, Sezer; Tao, Ran; van Gemert, Jan C; Gevers, Theo

2017-05-24

This work focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on the background instead of text regions. Once text regions are detected, they are further processed by two methods to perform text recognition i.e. ABBYY commercial OCR engine and a state-of-the-art character recognition algorithm. Then, to perform textual cue encoding, bi- and trigrams are formed between the recognized characters by considering the proposed spatial pairwise constraints. Finally, extracted visual and textual cues are combined for fine-grained classification. The proposed method is validated on four publicly available datasets: ICDAR03, ICDAR13, Con-Text and Flickr-logo. We improve the state-of-the-art end-to-end character recognition by a large margin of 15% on ICDAR03. We show that textual cues are useful in addition to visual cues for fine-grained classification. We show that textual cues are also useful for logo retrieval. Adding textual cues outperforms visual- and textual-only in fine-grained classification (70.7% to 60.3%) and logo retrieval (57.4% to 54.8%).

A Bayesian computational model for online character recognition and disability assessment during cursive eye writing.

PubMed

Diard, Julien; Rynik, Vincent; Lorenceau, Jean

2013-01-01

This research involves a novel apparatus, in which the user is presented with an illusion inducing visual stimulus. The user perceives illusory movement that can be followed by the eye, so that smooth pursuit eye movements can be sustained in arbitrary directions. Thus, free-flow trajectories of any shape can be traced. In other words, coupled with an eye-tracking device, this apparatus enables "eye writing," which appears to be an original object of study. We adapt a previous model of reading and writing to this context. We describe a probabilistic model called the Bayesian Action-Perception for Eye On-Line model (BAP-EOL). It encodes probabilistic knowledge about isolated letter trajectories, their size, high-frequency components of the produced trajectory, and pupil diameter. We show how Bayesian inference, in this single model, can be used to solve several tasks, like letter recognition and novelty detection (i.e., recognizing when a presented character is not part of the learned database). We are interested in the potential use of the eye writing apparatus by motor impaired patients: the final task we solve by Bayesian inference is disability assessment (i.e., measuring and tracking the evolution of motor characteristics of produced trajectories). Preliminary experimental results are presented, which illustrate the method, showing the feasibility of character recognition in the context of eye writing. We then show experimentally how a model of the unknown character can be used to detect trajectories that are likely to be new symbols, and how disability assessment can be performed by opportunistically observing characteristics of fine motor control, as letter are being traced. Experimental analyses also help identify specificities of eye writing, as compared to handwriting, and the resulting technical challenges.

A Bayesian computational model for online character recognition and disability assessment during cursive eye writing

PubMed Central

Diard, Julien; Rynik, Vincent; Lorenceau, Jean

2013-01-01

This research involves a novel apparatus, in which the user is presented with an illusion inducing visual stimulus. The user perceives illusory movement that can be followed by the eye, so that smooth pursuit eye movements can be sustained in arbitrary directions. Thus, free-flow trajectories of any shape can be traced. In other words, coupled with an eye-tracking device, this apparatus enables “eye writing,” which appears to be an original object of study. We adapt a previous model of reading and writing to this context. We describe a probabilistic model called the Bayesian Action-Perception for Eye On-Line model (BAP-EOL). It encodes probabilistic knowledge about isolated letter trajectories, their size, high-frequency components of the produced trajectory, and pupil diameter. We show how Bayesian inference, in this single model, can be used to solve several tasks, like letter recognition and novelty detection (i.e., recognizing when a presented character is not part of the learned database). We are interested in the potential use of the eye writing apparatus by motor impaired patients: the final task we solve by Bayesian inference is disability assessment (i.e., measuring and tracking the evolution of motor characteristics of produced trajectories). Preliminary experimental results are presented, which illustrate the method, showing the feasibility of character recognition in the context of eye writing. We then show experimentally how a model of the unknown character can be used to detect trajectories that are likely to be new symbols, and how disability assessment can be performed by opportunistically observing characteristics of fine motor control, as letter are being traced. Experimental analyses also help identify specificities of eye writing, as compared to handwriting, and the resulting technical challenges. PMID:24273525

Beyond Word Processing.

ERIC Educational Resources Information Center

Haight, Larry

1989-01-01

Types of specialty software that can help in computer editing are discussed, including programs for file transformation, optical character recognition, facsimile transmission, spell-checking, style assistance, editing, indexing, and headline-writing. (MSE)

Invariant approach to the character classification

NASA Astrophysics Data System (ADS)

Šariri, Kristina; Demoli, Nazif

2008-04-01

Image moments analysis is a very useful tool which allows image description invariant to translation and rotation, scale change and some types of image distortions. The aim of this work was development of simple method for fast and reliable classification of characters by using Hu's and affine moment invariants. Measure of Eucleidean distance was used as a discrimination feature with statistical parameters estimated. The method was tested in classification of Times New Roman font letters as well as sets of the handwritten characters. It is shown that using all Hu's and three affine invariants as discrimination set improves recognition rate by 30%.

Urdu Nasta'liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks.

PubMed

Naz, Saeeda; Umar, Arif Iqbal; Ahmed, Riaz; Razzak, Muhammad Imran; Rashid, Sheikh Faisal; Shafait, Faisal

2016-01-01

The recognition of Arabic script and its derivatives such as Urdu, Persian, Pashto etc. is a difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult due to its Nasta'liq writing style. Nasta'liq writing style inherits complex calligraphic nature, which presents major issues to recognition of Urdu text owing to diagonality in writing, high cursiveness, context sensitivity and overlapping of characters. Therefore, the work done for recognition of Arabic script cannot be directly applied to Urdu recognition. We present Multi-dimensional Long Short Term Memory (MDLSTM) Recurrent Neural Networks with an output layer designed for sequence labeling for recognition of printed Urdu text-lines written in the Nasta'liq writing style. Experiments show that MDLSTM attained a recognition accuracy of 98% for the unconstrained Urdu Nasta'liq printed text, which significantly outperforms the state-of-the-art techniques.

The impact of OCR accuracy on automated cancer classification of pathology reports.

PubMed

Zuccon, Guido; Nguyen, Anthony N; Bergheim, Anton; Wickman, Sandra; Grayson, Narelle

2012-01-01

To evaluate the effects of Optical Character Recognition (OCR) on the automatic cancer classification of pathology reports. Scanned images of pathology reports were converted to electronic free-text using a commercial OCR system. A state-of-the-art cancer classification system, the Medical Text Extraction (MEDTEX) system, was used to automatically classify the OCR reports. Classifications produced by MEDTEX on the OCR versions of the reports were compared with the classification from a human amended version of the OCR reports. The employed OCR system was found to recognise scanned pathology reports with up to 99.12% character accuracy and up to 98.95% word accuracy. Errors in the OCR processing were found to minimally impact on the automatic classification of scanned pathology reports into notifiable groups. However, the impact of OCR errors is not negligible when considering the extraction of cancer notification items, such as primary site, histological type, etc. The automatic cancer classification system used in this work, MEDTEX, has proven to be robust to errors produced by the acquisition of freetext pathology reports from scanned images through OCR software. However, issues emerge when considering the extraction of cancer notification items.

Automated extraction of radiation dose information from CT dose report images.

PubMed

Li, Xinhua; Zhang, Da; Liu, Bob

2011-06-01

The purpose of this article is to describe the development of an automated tool for retrieving texts from CT dose report images. Optical character recognition was adopted to perform text recognitions of CT dose report images. The developed tool is able to automate the process of analyzing multiple CT examinations, including text recognition, parsing, error correction, and exporting data to spreadsheets. The results were precise for total dose-length product (DLP) and were about 95% accurate for CT dose index and DLP of scanned series.

Offline Arabic handwriting recognition: a survey.

PubMed

Lorigo, Liana M; Govindaraju, Venu

2006-05-01

The automatic recognition of text on scanned images has enabled many applications such as searching for words in large volumes of documents, automatic sorting of postal mail, and convenient editing of previously printed documents. The domain of handwriting in the Arabic script presents unique technical challenges and has been addressed more recently than other domains. Many different methods have been proposed and applied to various types of images. This paper provides a comprehensive review of these methods. It is the first survey to focus on Arabic handwriting recognition and the first Arabic character recognition survey to provide recognition rates and descriptions of test data for the approaches discussed. It includes background on the field, discussion of the methods, and future research directions.

Big Data Quality Case Study Preliminary Findings, U.S. Army MEDCOM MODS

DTIC Science & Technology

2013-09-01

captured in electronic form is relatively small, on the order of hundreds of thousands of health profiles at say around 500K per profile, or in the...in electronic form, then different language identification, handwriting recognition, and Natural Language Processing (NLP) techniques could be used...and patterns” [15]. Volume - The free text fields vary in length from say ten characters to several hundred characters. Other materials can be much

Who was that masked man? Conjoint representations of intrinsic motions with actor appearance.

PubMed

Kersten, Alan W; Earles, Julie L; Negri, Leehe

2018-09-01

Motion plays an important role in recognising animate creatures. This research supports a distinction between intrinsic and extrinsic motions in their relationship to identifying information about the characters performing the motions. Participants viewed events involving costumed human characters. Intrinsic motions involved relative movements of a character's body parts, whereas extrinsic motions involved movements with respect to external landmarks. Participants were later tested for recognition of the motions and who had performed them. The critical test items involved familiar characters performing motions that had previously been performed by other characters. Participants falsely recognised extrinsic conjunction items, in which characters followed the paths of other characters, more often than intrinsic conjunction items, in which characters moved in the manner of other characters. In contrast, participants falsely recognised new extrinsic motions less often than new intrinsic motions, suggesting that they remembered extrinsic motions but had difficulty remembering who had performed them. Modelling of receiver operating characteristics indicated that participants discriminated old items from intrinsic conjunction items via familiarity, consistent with conjoint representations of intrinsic motion and identity information. In contrast, participants used recollection to distinguish old items from extrinsic conjunction items, consistent with separate but associated representations of extrinsic motion and identity information.

The time-course of lexical activation in Japanese morphographic word recognition: evidence for a character-driven processing model.

PubMed

Miwa, Koji; Libben, Gary; Dijkstra, Ton; Baayen, Harald

2014-01-01

This lexical decision study with eye tracking of Japanese two-kanji-character words investigated the order in which a whole two-character word and its morphographic constituents are activated in the course of lexical access, the relative contributions of the left and the right characters in lexical decision, the depth to which semantic radicals are processed, and how nonlinguistic factors affect lexical processes. Mixed-effects regression analyses of response times and subgaze durations (i.e., first-pass fixation time spent on each of the two characters) revealed joint contributions of morphographic units at all levels of the linguistic structure with the magnitude and the direction of the lexical effects modulated by readers' locus of attention in a left-to-right preferred processing path. During the early time frame, character effects were larger in magnitude and more robust than radical and whole-word effects, regardless of the font size and the type of nonwords. Extending previous radical-based and character-based models, we propose a task/decision-sensitive character-driven processing model with a level-skipping assumption: Connections from the feature level bypass the lower radical level and link up directly to the higher character level.

A neural network based artificial vision system for licence plate recognition.

PubMed

Draghici, S

1997-02-01

This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

Learning and Inductive Inference

DTIC Science & Technology

1982-07-01

a set of graph grammars to describe visual scenes . Other researchers have applied graph grammars to the pattern recognition of handwritten characters...345 1. Issues / 345 2. Mostows’ operationalizer / 350 0. Learning from ezamples / 360 1. Issues / 3t60 2. Learning in control and pattern recognition ...art.icleis on rote learntinig and ailvice- tAik g. K(ennieth Clarkson contributed Ltte article on grmvit atical inference, anid Geoff’ lroiney wrote

Enhancing surveillance for hepatitis C through public health informatics.

PubMed

Heisey-Grove, Dawn M; Church, Daniel R; Haney, Gillian A; Demaria, Alfred

2011-01-01

Disease surveillance for hepatitis C in the United States is limited by the occult nature of many of these infections, the large volume of cases, and limited public health resources. Through a series of discrete processes, the Massachusetts Department of Public Health modified its surveillance system in an attempt to improve timeliness and completeness of reporting and case follow-up of hepatitis C. These processes included clinician-based reporting, electronic laboratory reporting, deployment of a Web-based disease surveillance system, automated triage of pertinent data, and automated character recognition software for case-report processing. These changes have resulted in an increase in the timeliness of reporting.

ERPs reveal sub-lexical processing in Chinese character recognition.

PubMed

Wu, Yan; Mo, Deyuan; Tsang, Yiu-Kei; Chen, Hsuan-Chih

2012-04-18

The present study used ERPs and a lexical decision task to explore the roles of position-general and position-specific radicals and their relative time courses in processing Chinese characters. Two types of radical frequency were manipulated: the number of characters containing a specific radical irrespective of position (i.e., radical frequency or RF) and the number of characters containing a specific radical at a particular position (i.e., position-specific radical frequency or PRF). The PRF effect was found to be associated with P150, P200, and N400, whereas the RF effect was associated with P200. These results suggest that both position-general and position-specific radicals could influence character processing, but the effect of position-specific radicals appeared earlier and lasted longer than that of position-general radicals. These findings are interpreted in terms of the specific orthographic properties of the sub-lexical components of Chinese characters. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Character Recognition Using Novel Optoelectronic Neural Network

DTIC Science & Technology

1993-04-01

interest will include machine learning and perception. Permanent Address: William M. Robinson c/o Dave and Judy Bartine 117 Westcliff Drive Harriman, TN 37748 This thesis was typed by William M. Robinson. 190 END

Keyboarding: An Important Skill for the Office of the Future.

ERIC Educational Resources Information Center

Burford, Anna M.

1980-01-01

Defines the components of the office of the future: data processing, micrographics, optical character recognition, telecommunications, and word processing. Also discusses teacher responsibility, student preparation, future challenges, and teacher awareness. (CT)

Enter Words and Pictures the Easy Way--Scan Them.

ERIC Educational Resources Information Center

Olivas, Jerry

1989-01-01

Discusses image scanning and optical character recognition. Describes how computer scanners work. Summarizes scan quality, scanning speed requirements, and hardware requirements for scanners. Surveys the range of scanners currently available. (MVL)

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.

Distorted Character Recognition Via An Associative Neural Network

NASA Astrophysics Data System (ADS)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

Lexical processing of Chinese sub-character components: Semantic activation of phonetic radicals as revealed by the Stroop effect.

PubMed

Yeh, Su-Ling; Chou, Wei-Lun; Ho, Pokuan

2017-11-17

Most Chinese characters are compounds consisting of a semantic radical indicating semantic category and a phonetic radical cuing the pronunciation of the character. Controversy surrounds whether radicals also go through the same lexical processing as characters and, critically, whether phonetic radicals involve semantic activation since they can also be characters when standing alone. Here we examined these issues using the Stroop task whereby participants responded to the ink color of the character. The key finding was that Stroop effects were found when the character itself had a meaning unrelated to color, but contained a color name phonetic radical (e.g., "guess", with the phonetic radical "cyan", on the right) or had a meaning associated with color (e.g., "pity", with the phonetic radical "blood" on the right which has a meaning related to "red"). Such Stroop effects from the phonetic radical within a character unrelated to color support that Chinese character recognition involves decomposition of characters into their constituent radicals; with each of their meanings including phonetic radicals activated independently, even though it would inevitably interfere with that of the whole character. Compared with the morphological decomposition in English whereby the semantics of the morphemes are not necessarily activated, the unavoidable semantic activation of phonetic radicals represents a unique feature in Chinese character processing.

What Is in the Naming? A 5-Year Longitudinal Study of Early Rapid Naming and Phonological Sensitivity in Relation to Subsequent Reading Skills in Both Native Chinese and English as a Second Language

ERIC Educational Resources Information Center

Pan, Jinger; McBride-Chang, Catherine; Shu, Hua; Liu, Hongyun; Zhang, Yuping; Li, Hong

2011-01-01

Among 262 Chinese children, syllable awareness and rapid automatized naming (RAN) at age 5 years and invented spelling of Pinyin at age 6 years independently predicted subsequent Chinese character recognition and English word reading at ages 8 years and 10 years, even with initial Chinese character reading ability statistically controlled. In…

Grading Multiple Choice Exams with Low-Cost and Portable Computer-Vision Techniques

NASA Astrophysics Data System (ADS)

Fisteus, Jesus Arias; Pardo, Abelardo; García, Norberto Fernández

2013-08-01

Although technology for automatic grading of multiple choice exams has existed for several decades, it is not yet as widely available or affordable as it should be. The main reasons preventing this adoption are the cost and the complexity of the setup procedures. In this paper, Eyegrade, a system for automatic grading of multiple choice exams is presented. While most current solutions are based on expensive scanners, Eyegrade offers a truly low-cost solution requiring only a regular off-the-shelf webcam. Additionally, Eyegrade performs both mark recognition as well as optical character recognition of handwritten student identification numbers, which avoids the use of bubbles in the answer sheet. When compared with similar webcam-based systems, the user interface in Eyegrade has been designed to provide a more efficient and error-free data collection procedure. The tool has been validated with a set of experiments that show the ease of use (both setup and operation), the reduction in grading time, and an increase in the reliability of the results when compared with conventional, more expensive systems.

Methods for Presenting Braille Characters on a Mobile Device with a Touchscreen and Tactile Feedback.

PubMed

Rantala, J; Raisamo, R; Lylykangas, J; Surakka, V; Raisamo, J; Salminen, K; Pakkanen, T; Hippula, A

2009-01-01

Three novel interaction methods were designed for reading six-dot Braille characters from the touchscreen of a mobile device. A prototype device with a piezoelectric actuator embedded under the touchscreen was used to create tactile feedback. The three interaction methods, scan, sweep, and rhythm, enabled users to read Braille characters one at a time either by exploring the characters dot by dot or by sensing a rhythmic pattern presented on the screen. The methods were tested with five blind Braille readers as a proof of concept. The results of the first experiment showed that all three methods can be used to convey information as the participants could accurately (91-97 percent) recognize individual characters. In the second experiment the presentation rate of the most efficient and preferred method, the rhythm, was varied. A mean recognition accuracy of 70 percent was found when the speed of presenting a single character was nearly doubled from the first experiment. The results showed that temporal tactile feedback and Braille coding can be used to transmit single-character information while further studies are still needed to evaluate the presentation of serial information, i.e., multiple Braille characters.

Automatic detection and recognition of signs from natural scenes.

PubMed

Chen, Xilin; Yang, Jie; Zhang, Jing; Waibel, Alex

2004-01-01

In this paper, we present an approach to automatic detection and recognition of signs from natural scenes, and its application to a sign translation task. The proposed approach embeds multiresolution and multiscale edge detection, adaptive searching, color analysis, and affine rectification in a hierarchical framework for sign detection, with different emphases at each phase to handle the text in different sizes, orientations, color distributions and backgrounds. We use affine rectification to recover deformation of the text regions caused by an inappropriate camera view angle. The procedure can significantly improve text detection rate and optical character recognition (OCR) accuracy. Instead of using binary information for OCR, we extract features from an intensity image directly. We propose a local intensity normalization method to effectively handle lighting variations, followed by a Gabor transform to obtain local features, and finally a linear discriminant analysis (LDA) method for feature selection. We have applied the approach in developing a Chinese sign translation system, which can automatically detect and recognize Chinese signs as input from a camera, and translate the recognized text into English.

Review of chart recognition in document images

NASA Astrophysics Data System (ADS)

Liu, Yan; Lu, Xiaoqing; Qin, Yeyang; Tang, Zhi; Xu, Jianbo

2013-01-01

As an effective information transmitting way, chart is widely used to represent scientific statistics datum in books, research papers, newspapers etc. Though textual information is still the major source of data, there has been an increasing trend of introducing graphs, pictures, and figures into the information pool. Text recognition techniques for documents have been accomplished using optical character recognition (OCR) software. Chart recognition techniques as a necessary supplement of OCR for document images are still an unsolved problem due to the great subjectiveness and variety of charts styles. This paper reviews the development process of chart recognition techniques in the past decades and presents the focuses of current researches. The whole process of chart recognition is presented systematically, which mainly includes three parts: chart segmentation, chart classification, and chart Interpretation. In each part, the latest research work is introduced. In the last, the paper concludes with a summary and promising future research direction.

Arabic handwritten: pre-processing and segmentation

NASA Astrophysics Data System (ADS)

Maliki, Makki; Jassim, Sabah; Al-Jawad, Naseer; Sellahewa, Harin

2012-06-01

This paper is concerned with pre-processing and segmentation tasks that influence the performance of Optical Character Recognition (OCR) systems and handwritten/printed text recognition. In Arabic, these tasks are adversely effected by the fact that many words are made up of sub-words, with many sub-words there associated one or more diacritics that are not connected to the sub-word's body; there could be multiple instances of sub-words overlap. To overcome these problems we investigate and develop segmentation techniques that first segment a document into sub-words, link the diacritics with their sub-words, and removes possible overlapping between words and sub-words. We shall also investigate two approaches for pre-processing tasks to estimate sub-words baseline, and to determine parameters that yield appropriate slope correction, slant removal. We shall investigate the use of linear regression on sub-words pixels to determine their central x and y coordinates, as well as their high density part. We also develop a new incremental rotation procedure to be performed on sub-words that determines the best rotation angle needed to realign baselines. We shall demonstrate the benefits of these proposals by conducting extensive experiments on publicly available databases and in-house created databases. These algorithms help improve character segmentation accuracy by transforming handwritten Arabic text into a form that could benefit from analysis of printed text.

Computers for the Disabled.

ERIC Educational Resources Information Center

Lazzaro, Joseph J.

1993-01-01

Describes adaptive technology for personal computers that accommodate disabled users and may require special equipment including hardware, memory, expansion slots, and ports. Highlights include vision aids, including speech synthesizers, magnification, braille, and optical character recognition (OCR); hearing adaptations; motor-impaired…

Usage of the back-propagation method for alphabet recognition

NASA Astrophysics Data System (ADS)

Shaila Sree, R. N.; Eswaran, Kumar; Sundararajan, N.

1999-03-01

Artificial Neural Networks play a pivotal role in the branch of Artificial Intelligence. They can be trained efficiently for a variety of tasks using different methods, of which the Back Propagation method is one among them. The paper studies the choosing of various design parameters of a neural network for the Back Propagation method. The study shows that when these parameters are properly assigned, the training task of the net is greatly simplified. The character recognition problem has been chosen as a test case for this study. A sample space of different handwritten characters of the English alphabet was gathered. A Neural net is finally designed taking many the design aspects into consideration and trained for different styles of writing. Experimental results are reported and discussed. It has been found that an appropriate choice of the design parameters of the neural net for the Back Propagation method reduces the training time and improves the performance of the net.

Enantioselective recognition at mesoporous chiral metal surfaces.

PubMed

Wattanakit, Chularat; Côme, Yémima Bon Saint; Lapeyre, Veronique; Bopp, Philippe A; Heim, Matthias; Yadnum, Sudarat; Nokbin, Somkiat; Warakulwit, Chompunuch; Limtrakul, Jumras; Kuhn, Alexander

2014-01-01

Chirality is widespread in natural systems, and artificial reproduction of chiral recognition is a major scientific challenge, especially owing to various potential applications ranging from catalysis to sensing and separation science. In this context, molecular imprinting is a well-known approach for generating materials with enantioselective properties, and it has been successfully employed using polymers. However, it is particularly difficult to synthesize chiral metal matrices by this method. Here we report the fabrication of a chirally imprinted mesoporous metal, obtained by the electrochemical reduction of platinum salts in the presence of a liquid crystal phase and chiral template molecules. The porous platinum retains a chiral character after removal of the template molecules. A matrix obtained in this way exhibits a large active surface area due to its mesoporosity, and also shows a significant discrimination between two enantiomers, when they are probed using such materials as electrodes.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters.

PubMed

Rempel, David; Camilleri, Matt J; Lee, David L

2015-10-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.

A vision-based automated guided vehicle system with marker recognition for indoor use.

PubMed

Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

2013-08-07

We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.

Art critic: Multisignal vision and speech interaction system in a gaming context.

PubMed

Reale, Michael J; Liu, Peng; Yin, Lijun; Canavan, Shaun

2013-12-01

True immersion of a player within a game can only occur when the world simulated looks and behaves as close to reality as possible. This implies that the game must correctly read and understand, among other things, the player's focus, attitude toward the objects/persons in focus, gestures, and speech. In this paper, we proposed a novel system that integrates eye gaze estimation, head pose estimation, facial expression recognition, speech recognition, and text-to-speech components for use in real-time games. Both the eye gaze and head pose components utilize underlying 3-D models, and our novel head pose estimation algorithm uniquely combines scene flow with a generic head model. The facial expression recognition module uses the local binary patterns with three orthogonal planes approach on the 2-D shape index domain rather than the pixel domain, resulting in improved classification. Our system has also been extended to use a pan-tilt-zoom camera driven by the Kinect, allowing us to track a moving player. A test game, Art Critic, is also presented, which not only demonstrates the utility of our system but also provides a template for player/non-player character (NPC) interaction in a gaming context. The player alters his/her view of the 3-D world using head pose, looks at paintings/NPCs using eye gaze, and makes an evaluation based on the player's expression and speech. The NPC artist will respond with facial expression and synthetic speech based on its personality. Both qualitative and quantitative evaluations of the system are performed to illustrate the system's effectiveness.

An evaluation of information retrieval accuracy with simulated OCR output

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

Croft, W.B.; Harding, S.M.; Taghva, K.

Optical Character Recognition (OCR) is a critical part of many text-based applications. Although some commercial systems use the output from OCR devices to index documents without editing, there is very little quantitative data on the impact of OCR errors on the accuracy of a text retrieval system. Because of the difficulty of constructing test collections to obtain this data, we have carried out evaluation using simulated OCR output on a variety of databases. The results show that high quality OCR devices have little effect on the accuracy of retrieval, but low quality devices used with databases of short documents canmore » result in significant degradation.« less

Trainable multiscript orientation detection

NASA Astrophysics Data System (ADS)

Van Beusekom, Joost; Rangoni, Yves; Breuel, Thomas M.

2010-01-01

Detecting the correct orientation of document images is an important step in large scale digitization processes, as most subsequent document analysis and optical character recognition methods assume upright position of the document page. Many methods have been proposed to solve the problem, most of which base on ascender to descender ratio computation. Unfortunately, this cannot be used for scripts having no descenders nor ascenders. Therefore, we present a trainable method using character similarity to compute the correct orientation. A connected component based distance measure is computed to compare the characters of the document image to characters whose orientation is known. This allows to detect the orientation for which the distance is lowest as the correct orientation. Training is easily achieved by exchanging the reference characters by characters of the script to be analyzed. Evaluation of the proposed approach showed accuracy of above 99% for Latin and Japanese script from the public UW-III and UW-II datasets. An accuracy of 98.9% was obtained for Fraktur on a non-public dataset. Comparison of the proposed method to two methods using ascender / descender ratio based orientation detection shows a significant improvement.

A smart sensor architecture based on emergent computation in an array of outer-totalistic cells

NASA Astrophysics Data System (ADS)

Dogaru, Radu; Dogaru, Ioana; Glesner, Manfred

2005-06-01

A novel smart-sensor architecture is proposed, capable to segment and recognize characters in a monochrome image. It is capable to provide a list of ASCII codes representing the recognized characters from the monochrome visual field. It can operate as a blind's aid or for industrial applications. A bio-inspired cellular model with simple linear neurons was found the best to perform the nontrivial task of cropping isolated compact objects such as handwritten digits or characters. By attaching a simple outer-totalistic cell to each pixel sensor, emergent computation in the resulting cellular automata lattice provides a straightforward and compact solution to the otherwise computationally intensive problem of character segmentation. A simple and robust recognition algorithm is built in a compact sequential controller accessing the array of cells so that the integrated device can provide directly a list of codes of the recognized characters. Preliminary simulation tests indicate good performance and robustness to various distortions of the visual field.

When Children Learn Programming: Antecedents, Concepts and Outcomes.

ERIC Educational Resources Information Center

Shneiderman, Ben

1985-01-01

Discusses components of an educational plan which supports acquisition of computer programing skills by elementary school children, including antecedent knowledge required (sequencing, similarity, character recognition, part/whole relationships, conditional forms, repetition, and incrementation); initial programing concepts; and outcomes valuable…

Document Delivery: An Annotated Selective Bibliography.

ERIC Educational Resources Information Center

Khalil, Mounir A.; Katz, Suzanne R.

1992-01-01

Presents a selective annotated bibliography of 61 items that deal with topics related to document delivery, including networks; hypertext; interlibrary loan; computer security; electronic publishing; copyright; online catalogs; resource sharing; electronic mail; electronic libraries; optical character recognition; microcomputers; liability issues;…

Detection and recognition of analytes based on their crystallization patterns

DOEpatents

Morozov, Victor [Manassas, VA; Bailey, Charles L [Cross Junction, VA; Vsevolodov, Nikolai N [Kensington, MD; Elliott, Adam [Manassas, VA

2008-05-06

The invention contemplates a method for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization pattern") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. It has been shown that changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. It was also found that both the character of changer in the crystallization patter and the fact of such changes can be used as recognition elements in analysis of protein molecules.

Neural Network and Letter Recognition.

NASA Astrophysics Data System (ADS)

Lee, Hue Yeon

Neural net architectures and learning algorithms that recognize hand written 36 alphanumeric characters are studied. The thin line input patterns written in 32 x 32 binary array are used. The system is comprised of two major components, viz. a preprocessing unit and a Recognition unit. The preprocessing unit in turn consists of three layers of neurons; the U-layer, the V-layer, and the C -layer. The functions of the U-layer is to extract local features by template matching. The correlation between the detected local features are considered. Through correlating neurons in a plane with their neighboring neurons, the V-layer would thicken the on-cells or lines that are groups of on-cells of the previous layer. These two correlations would yield some deformation tolerance and some of the rotational tolerance of the system. The C-layer then compresses data through the 'Gabor' transform. Pattern dependent choice of center and wavelengths of 'Gabor' filters is the cause of shift and scale tolerance of the system. Three different learning schemes had been investigated in the recognition unit, namely; the error back propagation learning with hidden units, a simple perceptron learning, and a competitive learning. Their performances were analyzed and compared. Since sometimes the network fails to distinguish between two letters that are inherently similar, additional ambiguity resolving neural nets are introduced on top of the above main neural net. The two dimensional Fourier transform is used as the preprocessing and the perceptron is used as the recognition unit of the ambiguity resolver. One hundred different person's handwriting sets are collected. Some of these are used as the training sets and the remainders are used as the test sets. The correct recognition rate of the system increases with the number of training sets and eventually saturates at a certain value. Similar recognition rates are obtained for the above three different learning algorithms. The minimum error rate, 4.9% is achieved for alphanumeric sets when 50 sets are trained. With the ambiguity resolver, it is reduced to 2.5%. In case that only numeral sets are trained and tested, 2.0% error rate is achieved. When only alphabet sets are considered, the error rate is reduced to 1.1%.

The Influence of Brand Equity Characters on Children's Food Preferences and Choices.

PubMed

McGale, Lauren Sophie; Halford, Jason Christian Grovenor; Harrold, Joanne Alison; Boyland, Emma Jane

2016-10-01

To assess the influence of brand equity characters displayed on food packaging on children's food preferences and choices, 2 studies were conducted. Brand equity characters are developed specifically to represent a particular brand or product. Despite existing literature suggesting that promotional characters influence children's food choices, to date, no research has assessed the influence of brand equity characters specifically. We recruited 209 children 4-8 years of age from schools and childcare centers in the UK. In a mixed-measures design, the children were asked to rate their taste preferences and preferred snack choice for 3 matched food pairs, presented either with or without a brand equity character displayed on packaging. Study 1 addressed congruent food-character associations and study 2 addressed incongruent associations. Participants were also asked to rate their recognition and liking of characters used. Wilcoxon signed-rank tests and χ(2) analyses were used where appropriate. Children were significantly more likely to show a preference for foods with a brand equity character displayed on the packaging compared with a matched food without a brand equity character, for both congruent and incongruent food-character associations. The presence of a brand equity character also significantly influenced the children's within-pair preferences, within-pair choices, and overall snack choice (congruent associations only). Displaying brand equity characters promotes unhealthy food choices in children. The findings are consistent with those of studies exploring other types of promotional characters. In the context of a childhood obesity epidemic, the use of brand equity characters in the promotion of foods high in fat, salt, and sugar to children should be restricted. Copyright © 2016 Elsevier Inc. All rights reserved.

DRR is a teenager

NASA Astrophysics Data System (ADS)

Nagy, George

2008-01-01

The fifteenth anniversary of the first SPIE symposium (titled Character Recognition Technologies) on Document Recognition and Retrieval provides an opportunity to examine DRR's contributions to the development of document technologies. Many of the tools taken for granted today, including workable general purpose OCR, large-scale, semi-automatic forms processing, inter-format table conversion, and text mining, followed research presented at this venue. This occasion also affords an opportunity to offer tribute to the conference organizers and proceedings editors and to the coterie of professionals who regularly participate in DRR.

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

PubMed

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Meet The Simpsons: top-down effects in face learning.

PubMed

Bonner, Lesley; Burton, A Mike; Jenkins, Rob; McNeill, Allan; Vicki, Bruce

2003-01-01

We examined whether prior knowledge of a person affects the visual processes involved in learning a face. In two experiments, subjects were taught to associate human faces with characters they knew (from the TV show The Simpsons) or characters they did not (novel names). In each experiment, knowledge of the character predicted performance in a recognition memory test, relying only on old/new confidence ratings. In experiment 1, we established the technique and showed that there is a face-learning advantage for known people, even when face items are counterbalanced for familiarity across the experiment. In experiment 2 we replicated the effect in a setting which discouraged subjects from attending more to known than unknown people, and eliminated any visual association between face stimuli and a character from The Simpsons. We conclude that prior knowledge about a person can enhance learning of a new face.

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

PubMed Central

Zhao, Yu-Xiang; Chou, Chien-Hsing

2016-01-01

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

Image Segmentation of Historical Handwriting from Palm Leaf Manuscripts

NASA Astrophysics Data System (ADS)

Surinta, Olarik; Chamchong, Rapeeporn

Palm leaf manuscripts were one of the earliest forms of written media and were used in Southeast Asia to store early written knowledge about subjects such as medicine, Buddhist doctrine and astrology. Therefore, historical handwritten palm leaf manuscripts are important for people who like to learn about historical documents, because we can learn more experience from them. This paper presents an image segmentation of historical handwriting from palm leaf manuscripts. The process is composed of three steps: 1) background elimination to separate text and background by Otsu's algorithm 2) line segmentation and 3) character segmentation by histogram of image. The end result is the character's image. The results from this research may be applied to optical character recognition (OCR) in the future.

Automatic feature design for optical character recognition using an evolutionary search procedure.

PubMed

Stentiford, F W

1985-03-01

An automatic evolutionary search is applied to the problem of feature extraction in an OCR application. A performance measure based on feature independence is used to generate features which do not appear to suffer from peaking effects [17]. Features are extracted from a training set of 30 600 machine printed 34 class alphanumeric characters derived from British mail. Classification results on the training set and a test set of 10 200 characters are reported for an increasing number of features. A 1.01 percent forced decision error rate is obtained on the test data using 316 features. The hardware implementation should be cheap and fast to operate. The performance compares favorably with current low cost OCR page readers.

Improved document image segmentation algorithm using multiresolution morphology

NASA Astrophysics Data System (ADS)

Bukhari, Syed Saqib; Shafait, Faisal; Breuel, Thomas M.

2011-01-01

Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.

A robust omnifont open-vocabulary Arabic OCR system using pseudo-2D-HMM

NASA Astrophysics Data System (ADS)

Rashwan, Abdullah M.; Rashwan, Mohsen A.; Abdel-Hameed, Ahmed; Abdou, Sherif; Khalil, A. H.

2012-01-01

Recognizing old documents is highly desirable since the demand for quickly searching millions of archived documents has recently increased. Using Hidden Markov Models (HMMs) has been proven to be a good solution to tackle the main problems of recognizing typewritten Arabic characters. These attempts however achieved a remarkable success for omnifont OCR under very favorable conditions, they didn't achieve the same performance in practical conditions, i.e. noisy documents. In this paper we present an omnifont, large-vocabulary Arabic OCR system using Pseudo Two Dimensional Hidden Markov Model (P2DHMM), which is a generalization of the HMM. P2DHMM offers a more efficient way to model the Arabic characters, such model offer both minimal dependency on the font size/style (omnifont), and high level of robustness against noise. The evaluation results of this system are very promising compared to a baseline HMM system and best OCRs available in the market (Sakhr and NovoDynamics). The recognition accuracy of the P2DHMM classifier is measured against the classic HMM classifier, the average word accuracy rates for P2DHMM and HMM classifiers are 79% and 66% respectively. The overall system accuracy is measured against Sakhr and NovoDynamics OCR systems, the average word accuracy rates for P2DHMM, NovoDynamics, and Sakhr are 74%, 71%, and 61% respectively.

Neural network and letter recognition

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

Lee, Hue Yeon.

Neural net architectures and learning algorithms that recognize hand written 36 alphanumeric characters are studied. The thin line input patterns written in 32 x 32 binary array are used. The system is comprised of two major components, viz. a preprocessing unit and a Recognition unit. The preprocessing unit in turn consists of three layers of neurons; the U-layer, the V-layer, and the C-layer. The functions of the U-layer is to extract local features by template matching. The correlation between the detected local features are considered. Through correlating neurons in a plane with their neighboring neurons, the V-layer would thicken themore » on-cells or lines that are groups of on-cells of the previous layer. These two correlations would yield some deformation tolerance and some of the rotational tolerance of the system. The C-layer then compresses data through the Gabor transform. Pattern dependent choice of center and wavelengths of Gabor filters is the cause of shift and scale tolerance of the system. Three different learning schemes had been investigated in the recognition unit, namely; the error back propagation learning with hidden units, a simple perceptron learning, and a competitive learning. Their performances were analyzed and compared. Since sometimes the network fails to distinguish between two letters that are inherently similar, additional ambiguity resolving neural nets are introduced on top of the above main neural net. The two dimensional Fourier transform is used as the preprocessing and the perceptron is used as the recognition unit of the ambiguity resolver. One hundred different person's handwriting sets are collected. Some of these are used as the training sets and the remainders are used as the test sets.« less

Auditory temporal perceptual learning and transfer in Chinese-speaking children with developmental dyslexia.

PubMed

Zhang, Manli; Xie, Weiyi; Xu, Yanzhi; Meng, Xiangzhi

2018-03-01

Perceptual learning refers to the improvement of perceptual performance as a function of training. Recent studies found that auditory perceptual learning may improve phonological skills in individuals with developmental dyslexia in alphabetic writing system. However, whether auditory perceptual learning could also benefit the reading skills of those learning the Chinese logographic writing system is, as yet, unknown. The current study aimed to investigate the remediation effect of auditory temporal perceptual learning on Mandarin-speaking school children with developmental dyslexia. Thirty children with dyslexia were screened from a large pool of students in 3th-5th grades. They completed a series of pretests and then were assigned to either a non-training control group or a training group. The training group worked on a pure tone duration discrimination task for 7 sessions over 2 weeks with thirty minutes per session. Post-tests immediately after training and a follow-up test 2 months later were conducted. Analyses revealed a significant training effect in the training group relative to non-training group, as well as near transfer to the temporal interval discrimination task and far transfer to phonological awareness, character recognition and reading fluency. Importantly, the training effect and all the transfer effects were stable at the 2-month follow-up session. Further analyses found that a significant correlation between character recognition performance and learning rate mainly existed in the slow learning phase, the consolidation stage of perceptual learning, and this effect was modulated by an individuals' executive function. These findings indicate that adaptive auditory temporal perceptual learning can lead to learning and transfer effects on reading performance, and shed further light on the potential role of basic perceptual learning in the remediation and prevention of developmental dyslexia. Copyright © 2018 Elsevier Ltd. All rights reserved.

Research on pre-processing of QR Code

NASA Astrophysics Data System (ADS)

Sun, Haixing; Xia, Haojie; Dong, Ning

2013-10-01

QR code encodes many kinds of information because of its advantages: large storage capacity, high reliability, full arrange of utter-high-speed reading, small printing size and high-efficient representation of Chinese characters, etc. In order to obtain the clearer binarization image from complex background, and improve the recognition rate of QR code, this paper researches on pre-processing methods of QR code (Quick Response Code), and shows algorithms and results of image pre-processing for QR code recognition. Improve the conventional method by changing the Souvola's adaptive text recognition method. Additionally, introduce the QR code Extraction which adapts to different image size, flexible image correction approach, and improve the efficiency and accuracy of QR code image processing.

Effect of pattern complexity on the visual span for Chinese and alphabet characters

PubMed Central

Wang, Hui; He, Xuanzi; Legge, Gordon E.

2014-01-01

The visual span for reading is the number of letters that can be recognized without moving the eyes and is hypothesized to impose a sensory limitation on reading speed. Factors affecting the size of the visual span have been studied using alphabet letters. There may be common constraints applying to recognition of other scripts. The aim of this study was to extend the concept of the visual span to Chinese characters and to examine the effect of the greater complexity of these characters. We measured visual spans for Chinese characters and alphabet letters in the central vision of bilingual subjects. Perimetric complexity was used as a metric to quantify the pattern complexity of binary character images. The visual span tests were conducted with four sets of stimuli differing in complexity—lowercase alphabet letters and three groups of Chinese characters. We found that the size of visual spans decreased with increasing complexity, ranging from 10.5 characters for alphabet letters to 4.5 characters for the most complex Chinese characters studied. A decomposition analysis revealed that crowding was the dominant factor limiting the size of the visual span, and the amount of crowding increased with complexity. Errors in the spatial arrangement of characters (mislocations) had a secondary effect. We conclude that pattern complexity has a major effect on the size of the visual span, mediated in large part by crowding. Measuring the visual span for Chinese characters is likely to have high relevance to understanding visual constraints on Chinese reading performance. PMID:24993020

Searching for Judy: how small mysteries affect narrative processes and memory.

PubMed

Love, Jessica; McKoon, Gail; Gerrig, Richard J

2010-05-01

Current theories of text processing say little about how authors' narrative choices, including the introduction of small mysteries, can affect readers' narrative experiences. Gerrig, Love, and McKoon (2009) provided evidence that 1 type of small mystery-a character introduced without information linking him or her to the story-affects readers' moment-by-moment processing. For that project, participants read stories that introduced characters by proper name alone (e.g., "Judy") or with information connecting the character to the rest of the story (e.g., "our principal Judy"). In an online recognition probe task, responses to the character's name 3 lines after his or her introduction were faster when the character had not been introduced with connecting information, suggesting that the character remained accessible awaiting resolution. In the 4 experiments in this article, we extend our theoretical analysis of small mysteries. In Experiments 1 and 2, we found evidence that trait information (e.g., "daredevil Judy") is not sufficient to connect a character to a text. In Experiments 3 and 4, we found evidence that the moment-by-moment processing effects of such small mysteries also affect readers' memory for the stories. We interpret the results in terms of Kintsch's (1988) construction-integration model of discourse processing. PsycINFO Database Record (c) 2010 APA, all rights reserved.

ASM Based Synthesis of Handwritten Arabic Text Pages

PubMed Central

Al-Hamadi, Ayoub; Elzobi, Moftah; El-etriby, Sherif; Ghoneim, Ahmed

2015-01-01

Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system that automatically turns Arabic Unicode text into synthetic images of handwritten documents and detailed ground truth. Active Shape Models (ASMs) based on 28046 online samples were used for character synthesis and statistical properties were extracted from the IESK-arDB database to simulate baselines and word slant or skew. In the synthesis step ASM based representations are composed to words and text pages, smoothed by B-Spline interpolation and rendered considering writing speed and pen characteristics. Finally, we use the synthetic data to validate a segmentation method. An experimental comparison with the IESK-arDB database encourages to train and test document analysis related methods on synthetic samples, whenever no sufficient natural ground truthed data is available. PMID:26295059

ASM Based Synthesis of Handwritten Arabic Text Pages.

PubMed

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-Etriby, Sherif; Ghoneim, Ahmed

2015-01-01

Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system that automatically turns Arabic Unicode text into synthetic images of handwritten documents and detailed ground truth. Active Shape Models (ASMs) based on 28046 online samples were used for character synthesis and statistical properties were extracted from the IESK-arDB database to simulate baselines and word slant or skew. In the synthesis step ASM based representations are composed to words and text pages, smoothed by B-Spline interpolation and rendered considering writing speed and pen characteristics. Finally, we use the synthetic data to validate a segmentation method. An experimental comparison with the IESK-arDB database encourages to train and test document analysis related methods on synthetic samples, whenever no sufficient natural ground truthed data is available.

Simple and efficient method for region of interest value extraction from picture archiving and communication system viewer with optical character recognition software and macro program.

PubMed

Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck

2015-01-01

The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Document image cleanup and binarization

NASA Astrophysics Data System (ADS)

Wu, Victor; Manmatha, Raghaven

1998-04-01

Image binarization is a difficult task for documents with text over textured or shaded backgrounds, poor contrast, and/or considerable noise. Current optical character recognition (OCR) and document analysis technology do not handle such documents well. We have developed a simple yet effective algorithm for document image clean-up and binarization. The algorithm consists of two basic steps. In the first step, the input image is smoothed using a low-pass filter. The smoothing operation enhances the text relative to any background texture. This is because background texture normally has higher frequency than text does. The smoothing operation also removes speckle noise. In the second step, the intensity histogram of the smoothed image is computed and a threshold automatically selected as follows. For black text, the first peak of the histogram corresponds to text. Thresholding the image at the value of the valley between the first and second peaks of the histogram binarizes the image well. In order to reliably identify the valley, the histogram is smoothed by a low-pass filter before the threshold is computed. The algorithm has been applied to some 50 images from a wide variety of source: digitized video frames, photos, newspapers, advertisements in magazines or sales flyers, personal checks, etc. There are 21820 characters and 4406 words in these images. 91 percent of the characters and 86 percent of the words are successfully cleaned up and binarized. A commercial OCR was applied to the binarized text when it consisted of fonts which were OCR recognizable. The recognition rate was 84 percent for the characters and 77 percent for the words.

The Processing of Visual and Phonological Configurations of Chinese One- and Two-Character Words in a Priming Task of Semantic Categorization.

PubMed

Ma, Bosen; Wang, Xiaoyun; Li, Degao

2015-01-01

To separate the contribution of phonological from that of visual-orthographic information in the recognition of a Chinese word that is composed of one or two Chinese characters, we conducted two experiments in a priming task of semantic categorization (PTSC), in which length (one- or two-character words), relation, prime (related or unrelated prime-target pairs), and SOA (47, 87, or 187 ms) were manipulated. The prime was similar to the target in meaning or in visual configuration in Experiment A and in meaning or in pronunciation in Experiment B. The results indicate that the two-character words were similar to the one-character words but were less demanding of cognitive resources than the one-character words in the processing of phonological, visual-orthographic, and semantic information. The phonological primes had a facilitating effect at the SOA of 47 ms but an inhibitory effect at the SOA of 187 ms on the participants' reaction times; the visual-orthographic primes only had an inhibitory influence on the participants' reaction times at the SOA of 187 ms. The visual configuration of a Chinese word of one or two Chinese characters has its own contribution in helping retrieve the word's meanings; similarly, the phonological configuration of a one- or two-character word plays its own role in triggering activations of the word's semantic representations.

Neural networks and applications tutorial

NASA Astrophysics Data System (ADS)

Guyon, I.

1991-09-01

The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

Applications of Optical Scanners in an Academic Center.

ERIC Educational Resources Information Center

Molinari, Carol; Tannenbaum, Robert S.

1995-01-01

Describes optical scanners, including how the technology works; applications in data management and research; development of instructional materials; and providing community services. Discussion includes the three basic types of optical scanners: optical character recognition (OCR), optical mark readers (OMR), and graphic scanners. A sidebar…

Intelligent OCR Processing.

ERIC Educational Resources Information Center

Sun, Wei; And Others

1992-01-01

Identifies types and distributions of errors in text produced by optical character recognition (OCR) and proposes a process using machine learning techniques to recognize and correct errors in OCR texts. Results of experiments indicating that this strategy can reduce human interaction required for error correction are reported. (25 references)…

Report on the Sixth Workshop on Chinese Linguistics.

ERIC Educational Resources Information Center

Shen, Zhongwei

1987-01-01

Summarizes 10 presentations made at the workshop on a variety of topics including: classification of Chinese dialects; the importance of semantic units in tone sandhi; insights on Chinese character recognition among brain-damaged patients; and a cognitive approach to the study of Chinese grammar. (TR)

Art and Dream.

ERIC Educational Resources Information Center

Guo, Shesen

2003-01-01

A computer-assisted learning/teaching model is conceived with implications of constructivist theory and an analogy between the traditional art form Shuanghuang and the teaching/learning environment. The virtual character of the model interacts with the learner, in the form of human behavior and speech supported by recognition biometrics,…

P2 and behavioral effects of stroke count in Chinese characters: Evidence for an analytic and attentional view.

PubMed

Yang, Shasha; Zhang, Shunmei; Wang, Quanhong

2016-08-15

The inconsistent stroke-count effect in Chinese character recognition has resulted in an intense debate between the analytic and holistic views of character processing. The length effects of English words on behavioral responses and event-related potentials (ERPs) are similarly inconclusive. In this study, we identified any behavioral and ERP stroke-count effects when orthographic neighborhood sizes are balanced across three stroke counts. A delayed character-matching task was conducted while ERPs were recorded. The behavioral data indicated that both response latency and error rate increased with increasing stroke count. The ERP data showed higher P2 but lower N2 amplitudes in the large count than in the median count condition. A higher P2 can reflect increased attentional load and reduced attentional resource for processing each stroke because of the additional strokes in the large count condition. The behavioral and ERP effects of stroke count provide evidence for the analytic view of character processing but also provide evidence against the holistic view. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

First instalment in resolution of the Banksia spinulosa complex (Proteaceae): B. neoanglica, a new species supported by phenetic analysis, ecology and geography

PubMed Central

Stimpson, Margaret L.; Weston, Peter H.; Telford, Ian R.H.; Bruhl, Jeremy J.

2012-01-01

Abstract Taxa in the Banksia spinulosa Sm. complex (Proteaceae) have populations with sympatric, parapatric and allopatric distributions and unclear or disputed boundaries. Our hypothesis is that under biological, phenetic and diagnosable species concepts that each of the currently named taxa within the Banksia spinulosa complex is a separate species. Based on specimens collected as part of this study, and data recorded from specimens in six Australian herbaria, complemented by phenetic analysis (semi–strong multidimensional scaling and UPGMA clustering) and a detailed morphological study, we investigated both morphological variation and geographic distribution in the Banksia spinulosa complex. All specimens used for this study are held at the N.C.W. Beadle Herbarium or the National Herbarium of New South Wales. In total 23 morphological characters (11 quantitative, five binary, and seven multistate characters) were analysed phenetically for 89 specimens. Ordination and cluster analysis resulted in individuals grouping strongly allowing recognition of distinct groups consistent with their recognition as separate species. Additional morphological analysis was completed on all specimens using leaf, floral, fruit and stem morphology, providing clear cut diagnosable groups and strong support for the recognition of Banksia spinulosa var. cunninghamii and Banksia spinulosa var. neoanglica as species. PMID:23170073

Pre-orthographic character string processing and parietal cortex: a role for visual attention in reading?

PubMed

Lobier, Muriel; Peyrin, Carole; Le Bas, Jean-François; Valdois, Sylviane

2012-07-01

The visual front-end of reading is most often associated with orthographic processing. The left ventral occipito-temporal cortex seems to be preferentially tuned for letter string and word processing. In contrast, little is known of the mechanisms responsible for pre-orthographic processing: the processing of character strings regardless of character type. While the superior parietal lobule has been shown to be involved in multiple letter processing, further data is necessary to extend these results to non-letter characters. The purpose of this study is to identify the neural correlates of pre-orthographic character string processing independently of character type. Fourteen skilled adult readers carried out multiple and single element visual categorization tasks with alphanumeric (AN) and non-alphanumeric (nAN) characters under fMRI. The role of parietal cortex in multiple element processing was further probed with a priori defined anatomical regions of interest (ROIs). Participants activated posterior parietal cortex more strongly for multiple than single element processing. ROI analyses showed that bilateral SPL/BA7 was more strongly activated for multiple than single element processing, regardless of character type. In contrast, no multiple element specific activity was found in inferior parietal lobules. These results suggests that parietal mechanisms are involved in pre-orthographic character string processing. We argue that in general, attentional mechanisms are involved in visual word recognition, as an early step of word visual analysis. Copyright © 2012 Elsevier Ltd. All rights reserved.

Trigram-based algorithms for OCR result correction

NASA Astrophysics Data System (ADS)

Bulatov, Konstantin; Manzhikov, Temudzhin; Slavin, Oleg; Faradjev, Igor; Janiszewski, Igor

2017-03-01

In this paper we consider a task of improving optical character recognition (OCR) results of document fields on low-quality and average-quality images using N-gram models. Cyrillic fields of Russian Federation internal passport are analyzed as an example. Two approaches are presented: the first one is based on hypothesis of dependence of a symbol from two adjacent symbols and the second is based on calculation of marginal distributions and Bayesian networks computation. A comparison of the algorithms and experimental results within a real document OCR system are presented, it's showed that the document field OCR accuracy can be improved by more than 6% for low-quality images.

Digital imaging technology assessment: Digital document storage project

NASA Technical Reports Server (NTRS)

1989-01-01

An ongoing technical assessment and requirements definition project is examining the potential role of digital imaging technology at NASA's STI facility. The focus is on the basic components of imaging technology in today's marketplace as well as the components anticipated in the near future. Presented is a requirement specification for a prototype project, an initial examination of current image processing at the STI facility, and an initial summary of image processing projects at other sites. Operational imaging systems incorporate scanners, optical storage, high resolution monitors, processing nodes, magnetic storage, jukeboxes, specialized boards, optical character recognition gear, pixel addressable printers, communications, and complex software processes.

Dense modifiable interconnections utilizing photorefractive volume holograms

NASA Astrophysics Data System (ADS)

Psaltis, Demetri; Qiao, Yong

1990-11-01

This report describes an experimental two-layer optical neural network built at Caltech. The system uses photorefractive volume holograms to implement dense, modifiable synaptic interconnections and liquid crystal light valves (LCVS) to perform nonlinear thresholding operations. Kanerva's Sparse, Distributed Memory was implemented using this network and its ability to recognize handwritten character-alphabet (A-Z) has been demonstrated experimentally. According to Kanerva's model, the first layer has fixed, random weights of interconnections and the second layer is trained by sum-of-outer-products rule. After training, the recognition rates of the network on the training set (104 patterns) and test set (520 patterns) are 100 and 50 percent, respectively.

Recognition of the genus Thaumatophyllum Schott − formerly Philodendron subg. Meconostigma (Araceae) − based on molecular and morphological evidence

PubMed Central

Sakuragui, Cassia Mônica; Calazans, Luana Silva Braucks; de Oliveira, Leticia Loss; de Morais, Érica Barroso; Benko-Iseppon, Ana Maria; Vasconcelos, Santelmo; Schrago, Carlos Eduardo Guerra; Mayo, Simon Joseph

2018-01-01

Abstract Philodendron subgenus Meconostigma has been a well-circumscribed group since 1829. Members of this group are easily distinguished by diagnostic morphological characters as well as by a distinct ecology and geographical distribution. Based on molecular, morphological and cytological evidence, we propose the recognition of P. subg. Meconostigma as a distinct genus, Thaumatophyllum Schott. We also present the necessary new combinations, an emended key and some nomenclatural and taxonomic corrections regarding 21 names of Thaumatophyllum. PMID:29750071

Relationships among Constructs of L2 Chinese Reading and Language Background

ERIC Educational Resources Information Center

Hsu, Wei-Li

2016-01-01

Extensive research has been conducted on the relationships of Chinese-character recognition to reading development; strategic competence to reading comprehension; and home linguistic exposure to heritage language acquisition. However, studies of these relationships have been marked by widely divergent theoretical underpinnings, and their results…

High Tech and Library Access for People with Disabilities.

ERIC Educational Resources Information Center

Roatch, Mary A.

1992-01-01

Describes tools that enable people with disabilities to access print information, including optical character recognition, synthetic voice output, other input devices, Braille access devices, large print displays, television and video, TDD (Telecommunications Devices for the Deaf), and Telebraille. Use of technology by libraries to meet mandates…

Storing and Viewing Electronic Documents.

ERIC Educational Resources Information Center

Falk, Howard

1999-01-01

Discusses the conversion of fragile library materials to computer storage and retrieval to extend the life of the items and to improve accessibility through the World Wide Web. Highlights include entering the images, including scanning; optical character recognition; full text and manual indexing; and available document- and image-management…

Data Input for Libraries: State-of-the-Art Report.

ERIC Educational Resources Information Center

Buckland, Lawrence F.

This brief overview of new manuscript preparation methods which allow authors and editors to set their own type discusses the advantages and disadvantages of optical character recognition (OCR), microcomputers and personal computers, minicomputers, and word processors for editing and database entry. Potential library applications are also…

Intelligent Classification in Huge Heterogeneous Data Sets

DTIC Science & Technology

2015-06-01

Competencies DoD Department of Defense GMTI Ground Moving Target Indicator ISR Intelligence, Surveillance and Reconnaissance NCD Noncoherent Change...Detection OCR Optical Character Recognition PCA Principal Component Analysis SAR Synthetic Aperture Radar SVD Singular Value Decomponsition USPS United States Postal Service 8 Approved for Public Release; Distribution Unlimited.

Warped document image correction method based on heterogeneous registration strategies

NASA Astrophysics Data System (ADS)

Tong, Lijing; Zhan, Guoliang; Peng, Quanyao; Li, Yang; Li, Yifan

2013-03-01

With the popularity of digital camera and the application requirement of digitalized document images, using digital cameras to digitalize document images has become an irresistible trend. However, the warping of the document surface impacts on the quality of the Optical Character Recognition (OCR) system seriously. To improve the warped document image's vision quality and the OCR rate, this paper proposed a warped document image correction method based on heterogeneous registration strategies. This method mosaics two warped images of the same document from different viewpoints. Firstly, two feature points are selected from one image. Then the two feature points are registered in the other image base on heterogeneous registration strategies. At last, image mosaics are done for the two images, and the best mosaiced image is selected by OCR recognition results. As a result, for the best mosaiced image, the distortions are mostly removed and the OCR results are improved markedly. Experimental results show that the proposed method can resolve the issue of warped document image correction more effectively.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters

PubMed Central

Rempel, David; Camilleri, Matt J.; Lee, David L.

2015-01-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input. PMID:26028955

An Image Processing Approach to Linguistic Translation

NASA Astrophysics Data System (ADS)

Kubatur, Shruthi; Sreehari, Suhas; Hegde, Rajeshwari

2011-12-01

The art of translation is as old as written literature. Developments since the Industrial Revolution have influenced the practice of translation, nurturing schools, professional associations, and standard. In this paper, we propose a method of translation of typed Kannada text (taken as an image) into its equivalent English text. The National Instruments (NI) Vision Assistant (version 8.5) has been used for Optical character Recognition (OCR). We developed a new way of transliteration (which we call NIV transliteration) to simplify the training of characters. Also, we build a special type of dictionary for the purpose of translation.

The pandemonium system of reflective agents.

PubMed

Smieja, F

1996-01-01

The Pandemonium system of reflective MINOS agents solves problems by automatic dynamic modularization of the input space. The agents contain feedforward neural networks which adapt using the backpropagation algorithm. We demonstrate the performance of Pandemonium on various categories of problems. These include learning continuous functions with discontinuities, separating two spirals, learning the parity function, and optical character recognition. It is shown how strongly the advantages gained from using a modularization technique depend on the nature of the problem. The superiority of the Pandemonium method over a single net on the first two test categories is contrasted with its limited advantages for the second two categories. In the first case the system converges quicker with modularization and is seen to lead to simpler solutions. For the second case the problem is not significantly simplified through flat decomposition of the input space, although convergence is still quicker.

EEG based topography analysis in string recognition task

NASA Astrophysics Data System (ADS)

Ma, Xiaofei; Huang, Xiaolin; Shen, Yuxiaotong; Qin, Zike; Ge, Yun; Chen, Ying; Ning, Xinbao

2017-03-01

Vision perception and recognition is a complex process, during which different parts of brain are involved depending on the specific modality of the vision target, e.g. face, character, or word. In this study, brain activities in string recognition task compared with idle control state are analyzed through topographies based on multiple measurements, i.e. sample entropy, symbolic sample entropy and normalized rhythm power, extracted from simultaneously collected scalp EEG. Our analyses show that, for most subjects, both symbolic sample entropy and normalized gamma power in string recognition task are significantly higher than those in idle state, especially at locations of P4, O2, T6 and C4. It implies that these regions are highly involved in string recognition task. Since symbolic sample entropy measures complexity, from the perspective of new information generation, and normalized rhythm power reveals the power distributions in frequency domain, complementary information about the underlying dynamics can be provided through the two types of indices.

Word Processing Programs and Weaker Writers/Readers: A Meta-Analysis of Research Findings

ERIC Educational Resources Information Center

Morphy, Paul; Graham, Steve

2012-01-01

Since its advent word processing has become a common writing tool, providing potential advantages over writing by hand. Word processors permit easy revision, produce legible characters quickly, and may provide additional supports (e.g., spellcheckers, speech recognition). Such advantages should remedy common difficulties among weaker…

Choosing a Scanner: Points To Consider before Buying a Scanner.

ERIC Educational Resources Information Center

Raby, Chris

1998-01-01

Outlines ten factors to consider before buying a scanner: size of document; type of document; color; speed and volume; resolution; image enhancement; image compression; optical character recognition; scanning subsystem; and the option to use a commercial bureau service. The importance of careful analysis of requirements is emphasized. (AEF)

12 CFR Supplement I to Part 1005 - Official Interpretations

Code of Federal Regulations, 2013 CFR

2013-01-01

... used to capture the Magnetic Ink Character Recognition (MICR) encoding to initiate a one-time automated clearinghouse (ACH) debit. For example, if a consumer authorizes a one-time ACH debit from the consumer's... involved at the time of the transaction, if the consumer's asset account is subsequently debited for the...

12 CFR Supplement I to Part 1005 - Official Interpretations

Code of Federal Regulations, 2012 CFR

2012-01-01

... used to capture the Magnetic Ink Character Recognition (MICR) encoding to initiate a one-time automated clearinghouse (ACH) debit. For example, if a consumer authorizes a one-time ACH debit from the consumer's... involved at the time of the transaction, if the consumer's asset account is subsequently debited for the...

Modelling Human Emotions for Tactical Decision-Making Games

ERIC Educational Resources Information Center

Visschedijk, Gillian C.; Lazonder, Ard W.; van der Hulst, Anja; Vink, Nathalie; Leemkuil, Henny

2013-01-01

The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studies were performed to investigate the relation between fidelity and human emotion recognition in virtual human characters. Study 1 compared five versions of a virtual…

Techniques of Document Management: A Review of Text Retrieval and Related Technologies.

ERIC Educational Resources Information Center

Veal, D. C.

2001-01-01

Reviews present and possible future developments in the techniques of electronic document management, the major ones being text retrieval and scanning and OCR (optical character recognition). Also addresses document acquisition, indexing and thesauri, publishing and dissemination standards, impact of the Internet, and the document management…

Natural Language Video Description using Deep Recurrent Neural Networks

DTIC Science & Technology

2015-11-23

records who says what, but lacks tim- ing information. Movie scripts typically include names of all characters and most movies loosely follow the...and Jürgen Schmidhuber. A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks. In Proc. 9th Int

7 CFR 278.5 - Participation of insured financial institutions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... the appropriate field on the redemption certificate using Magnetic Ink Character Recognition (MICR...-521). (3) Redeemed coupons must be indelibly cancelled on the face of the coupon by the first insured financial institution receiving them. If the cancellation on the coupon face does not show the depositing...

7 CFR 278.5 - Participation of insured financial institutions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... the appropriate field on the redemption certificate using Magnetic Ink Character Recognition (MICR...-521). (3) Redeemed coupons must be indelibly cancelled on the face of the coupon by the first insured financial institution receiving them. If the cancellation on the coupon face does not show the depositing...

7 CFR 278.5 - Participation of insured financial institutions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... the appropriate field on the redemption certificate using Magnetic Ink Character Recognition (MICR...-521). (3) Redeemed coupons must be indelibly cancelled on the face of the coupon by the first insured financial institution receiving them. If the cancellation on the coupon face does not show the depositing...

7 CFR 278.5 - Participation of insured financial institutions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... the appropriate field on the redemption certificate using Magnetic Ink Character Recognition (MICR...-521). (3) Redeemed coupons must be indelibly cancelled on the face of the coupon by the first insured financial institution receiving them. If the cancellation on the coupon face does not show the depositing...

7 CFR 278.5 - Participation of insured financial institutions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... the appropriate field on the redemption certificate using Magnetic Ink Character Recognition (MICR...-521). (3) Redeemed coupons must be indelibly cancelled on the face of the coupon by the first insured financial institution receiving them. If the cancellation on the coupon face does not show the depositing...

Food brand recognition and BMI in preschoolers.

PubMed

Harrison, Kristen; Moorman, Jessica; Peralta, Mericarmen; Fayhee, Kally

2017-07-01

Children's food brand recognition predicts health-related outcomes such as preference for obesogenic foods and increased risk for overweight. However, it is uncertain to what degree food brand recognition acts as a proxy for other factors such as parental education and income, child vocabulary, child age, child race/ethnicity, parent healthy eating guidance, child commercial TV viewing, and child dietary intake, all of which may influence or be influenced by food brand recognition. U.S. preschoolers (N = 247, average age 56 months) were measured for BMI and completed the Peabody Picture Vocabulary Test plus recognition and recall measures for a selection of U.S. food brands. Parents completed measures of healthy eating guidance, child dietary intake, child commercial TV viewing, parent education, household income, parent BMI, and child age and race/ethnicity. Controlling these variables, child food brand recognition predicted higher child BMI percentile. Further, qualitative examination of children's incorrect answers to recall items demonstrated perceptual confusion between brand mascots and other fantasy characters to which children are exposed during the preschool years, extending theory on child consumer development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ancestral State Reconstruction Reveals Rampant Homoplasy of Diagnostic Morphological Characters in Urticaceae, Conflicting with Current Classification Schemes

PubMed Central

Wu, Zeng-Yuan; Milne, Richard I.; Chen, Chia-Jui; Liu, Jie; Wang, Hong; Li, De-Zhu

2015-01-01

Urticaceae is a family with more than 2000 species, which contains remarkable morphological diversity. It has undergone many taxonomic reorganizations, and is currently the subject of further systematic studies. To gain more resolution in systematic studies and to better understand the general patterns of character evolution in Urticaceae, based on our previous phylogeny including 169 accessions comprising 122 species across 47 Urticaceae genera, we examined 19 diagnostic characters, and analysed these employing both maximum-parsimony and maximum-likelihood approaches. Our results revealed that 16 characters exhibited multiple state changes within the family, with ten exhibiting >eight changes and three exhibiting between 28 and 40. Morphological synapomorphies were identified for many clades, but the diagnostic value of these was often limited due to reversals within the clade and/or homoplasies elsewhere. Recognition of the four clades comprising the family at subfamily level can be supported by a small number carefully chosen defining traits for each. Several non-monophyletic genera appear to be defined only by characters that are plesiomorphic within their clades, and more detailed work would be valuable to find defining traits for monophyletic clades within these. Some character evolution may be attributed to adaptive evolution in Urticaceae due to shifts in habitat or vegetation type. This study demonstrated the value of using phylogeny to trace character evolution, and determine the relative importance of morphological traits for classification. PMID:26529598

Searching for Judy: How small mysteries affect narrative processes and memory

PubMed Central

Love, Jessica; McKoon, Gail; Gerrig, Richard J.

2010-01-01

Current theories of text processing say little about how author’s narrative choices, including the introduction of small mysteries, can affect readers’ narrative experiences. Gerrig, Love, and McKoon (2009) provided evidence that one type of small mystery—a character introduced without information linking him or her to the story—affects readers’ moment-by-moment processing. For that project, participants read stories that introduced characters by proper name alone (e.g., Judy) or with information connecting the character to the rest of the story (e.g., our principal Judy). In an on-line recognition probe task, responses to the character’s name three lines after his or her introduction were faster when the character had not been introduced with connecting information, suggesting that the character remained accessible awaiting resolution. In the four experiments in this paper, we extended our theoretical analysis of small mysteries. In Experiments 1 and 2, we found evidence that trait information (e.g., daredevil Judy) is not sufficient to connect a character to a text. In Experiments 3 and 4, we provide evidence that the moment-by-moment processing effects of such small mysteries also affect readers’ memory for the stories. We interpret the results in terms of Kintsch’s Construction-Integration model (1988) of discourse processing. PMID:20438273

Language experience shapes early electrophysiological responses to visual stimuli: the effects of writing system, stimulus length, and presentation duration.

PubMed

Xue, Gui; Jiang, Ting; Chen, Chuansheng; Dong, Qi

2008-02-15

How language experience affects visual word recognition has been a topic of intense interest. Using event-related potentials (ERPs), the present study compared the early electrophysiological responses (i.e., N1) to familiar and unfamiliar writings under different conditions. Thirteen native Chinese speakers (with English as their second language) were recruited to passively view four types of scripts: Chinese (familiar logographic writings), English (familiar alphabetic writings), Korean Hangul (unfamiliar logographic writings), and Tibetan (unfamiliar alphabetic writings). Stimuli also differed in lexicality (words vs. non-words, for familiar writings only), length (characters/letters vs. words), and presentation duration (100 ms vs. 750 ms). We found no significant differences between words and non-words, and the effect of language experience (familiar vs. unfamiliar) was significantly modulated by stimulus length and writing system, and to a less degree, by presentation duration. That is, the language experience effect (i.e., a stronger N1 response to familiar writings than to unfamiliar writings) was significant only for alphabetic letters, but not for alphabetic and logographic words. The difference between Chinese characters and unfamiliar logographic characters was significant under the condition of short presentation duration, but not under the condition of long presentation duration. Long stimuli elicited a stronger N1 response than did short stimuli, but this effect was significantly attenuated for familiar writings. These results suggest that N1 response might not reliably differentiate familiar and unfamiliar writings. More importantly, our results suggest that N1 is modulated by visual, linguistic, and task factors, which has important implications for the visual expertise hypothesis.

Developing Character and Values for Global Citizens: Analysis of pre-service science teachers' moral reasoning on socioscientific issues

NASA Astrophysics Data System (ADS)

Lee, Hyunju; Chang, Hyunsook; Choi, Kyunghee; Kim, Sung-Won; Zeidler, Dana L.

2012-04-01

Character and values are the essential driving forces that serve as general guides or points of reference for individuals to support decision-making and to act responsibly about global socioscientific issues (SSIs). Based on this assumption, we investigated to what extent pre-service science teachers (PSTs) of South Korea possess character and values as global citizens; these values include ecological worldview, socioscientific accountability, and social and moral compassion. Eighteen PSTs participated in the SSI programs focusing on developing character and values through dialogical and reflective processes. SSIs were centered on the use of nuclear power generation, climate change, and embryonic stem cell research. The results indicated that PSTs showed three key elements of character and values, but failed to apply consistent moral principles on the issues and demonstrated limited global perspectives. While they tended to approach the issues with emotion and sympathy, they nonetheless failed to perceive themselves as major moral agents who are able to actively resolve large-scale societal issues. This study also suggests that the SSI programs can facilitate socioscientific reasoning to include abilities such as recognition of the complexity of SSIs, examine issues from multiple perspectives, and exhibit skepticism about information.

Alternating-script priming in Japanese: Are Katakana and Hiragana characters interchangeable?

PubMed

Perea, Manuel; Nakayama, Mariko; Lupker, Stephen J

2017-07-01

Models of written word recognition in languages using the Roman alphabet assume that a word's visual form is quickly mapped onto abstract units. This proposal is consistent with the finding that masked priming effects are of similar magnitude from lowercase, uppercase, and alternating-case primes (e.g., beard-BEARD, BEARD-BEARD, and BeArD-BEARD). We examined whether this claim can be readily generalized to the 2 syllabaries of Japanese Kana (Hiragana and Katakana). The specific rationale was that if the visual form of Kana words is lost early in the lexical access process, alternating-script repetition primes should be as effective as same-script repetition primes at activating a target word. Results showed that alternating-script repetition primes were less effective at activating lexical representations of Katakana words than same-script repetition primes-indeed, they were no more effective than partial primes that contained only the Katakana characters from the alternating-script primes. Thus, the idiosyncrasies of each writing system do appear to shape the pathways to lexical access. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Toward a Computer Vision-based Wayfinding Aid for Blind Persons to Access Unfamiliar Indoor Environments.

PubMed

Tian, Yingli; Yang, Xiaodong; Yi, Chucai; Arditi, Aries

2013-04-01

Independent travel is a well known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a lab, or a bathroom) and other building amenities (e.g. an exit or an elevator), we incorporate object detection with text recognition. First we develop a robust and efficient algorithm to detect doors, elevators, and cabinets based on their general geometric shape, by combining edges and corners. The algorithm is general enough to handle large intra-class variations of objects with different appearances among different indoor environments, as well as small inter-class differences between different objects such as doors and door-like cabinets. Next, in order to distinguish intra-class objects (e.g. an office door from a bathroom door), we extract and recognize text information associated with the detected objects. For text recognition, we first extract text regions from signs with multiple colors and possibly complex backgrounds, and then apply character localization and topological analysis to filter out background interference. The extracted text is recognized using off-the-shelf optical character recognition (OCR) software products. The object type, orientation, location, and text information are presented to the blind traveler as speech.

Vehicle license plate recognition in dense fog based on improved atmospheric scattering model

NASA Astrophysics Data System (ADS)

Tang, Chunming; Lin, Jun; Chen, Chunkai; Dong, Yancheng

2018-04-01

An effective method based on improved atmospheric scattering model is proposed in this paper to handle the problem of the vehicle license plate location and recognition in dense fog. Dense fog detection is performed firstly by the top-hat transformation and the vertical edge detection, and the moving vehicle image is separated from the traffic video image. After the vehicle image is decomposed into two layers: structure and texture layers, the glow layer is separated from the structure layer to get the background layer. Followed by performing the mean-pooling and the bicubic interpolation algorithm, the atmospheric light map of the background layer can be predicted, meanwhile the transmission of the background layer is estimated through the grayed glow layer, whose gray value is altered by linear mapping. Then, according to the improved atmospheric scattering model, the final restored image can be obtained by fusing the restored background layer and the optimized texture layer. License plate location is performed secondly by a series of morphological operations, connected domain analysis and various validations. Characters extraction is achieved according to the projection. Finally, an offline trained pattern classifier of hybrid discriminative restricted boltzmann machines (HDRBM) is applied to recognize the characters. Experimental results on thorough data sets are reported to demonstrate that the proposed method can achieve high recognition accuracy and works robustly in the dense fog traffic environment during 24h or one day.

Toward a Computer Vision-based Wayfinding Aid for Blind Persons to Access Unfamiliar Indoor Environments

PubMed Central

Tian, YingLi; Yang, Xiaodong; Yi, Chucai; Arditi, Aries

2012-01-01

Independent travel is a well known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a lab, or a bathroom) and other building amenities (e.g. an exit or an elevator), we incorporate object detection with text recognition. First we develop a robust and efficient algorithm to detect doors, elevators, and cabinets based on their general geometric shape, by combining edges and corners. The algorithm is general enough to handle large intra-class variations of objects with different appearances among different indoor environments, as well as small inter-class differences between different objects such as doors and door-like cabinets. Next, in order to distinguish intra-class objects (e.g. an office door from a bathroom door), we extract and recognize text information associated with the detected objects. For text recognition, we first extract text regions from signs with multiple colors and possibly complex backgrounds, and then apply character localization and topological analysis to filter out background interference. The extracted text is recognized using off-the-shelf optical character recognition (OCR) software products. The object type, orientation, location, and text information are presented to the blind traveler as speech. PMID:23630409

Apparatus for detecting and recognizing analytes based on their crystallization patterns

DOEpatents

Morozov, Victor; Bailey, Charles L.; Vsevolodov, Nikolai N.; Elliott, Adam

2010-12-14

The invention contemplates apparatuses for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization patterns") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. Changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. Also, changes in the crystallization patterns, as well as the character of such changes, can be used as recognition elements in analysis of protein molecules.

Font adaptive word indexing of modern printed documents.

PubMed

Marinai, Simone; Marino, Emanuele; Soda, Giovanni

2006-08-01

We propose an approach for the word-level indexing of modern printed documents which are difficult to recognize using current OCR engines. By means of word-level indexing, it is possible to retrieve the position of words in a document, enabling queries involving proximity of terms. Web search engines implement this kind of indexing, allowing users to retrieve Web pages on the basis of their textual content. Nowadays, digital libraries hold collections of digitized documents that can be retrieved either by browsing the document images or relying on appropriate metadata assembled by domain experts. Word indexing tools would therefore increase the access to these collections. The proposed system is designed to index homogeneous document collections by automatically adapting to different languages and font styles without relying on OCR engines for character recognition. The approach is based on three main ideas: the use of Self Organizing Maps (SOM) to perform unsupervised character clustering, the definition of one suitable vector-based word representation whose size depends on the word aspect-ratio, and the run-time alignment of the query word with indexed words to deal with broken and touching characters. The most appropriate applications are for processing modern printed documents (17th to 19th centuries) where current OCR engines are less accurate. Our experimental analysis addresses six data sets containing documents ranging from books of the 17th century to contemporary journals.

Semantic vs. Phonetic Decoding Strategies in Non-Native Readers of Chinese

ERIC Educational Resources Information Center

Williams, Clay H.

2010-01-01

This dissertation examines the effects of semantic and phonetic radicals on Chinese character decoding by high-intermediate level Chinese as a Foreign Language (CFL) learners. The results of the main study (discussed in Chapter #5) suggest that the CFL learners tested have a well-developed semantic pathway to recognition; however, their…

Proficient Readers' Reading Behavior in Taiwan: The Study of Young Chinese Readers

ERIC Educational Resources Information Center

Chang, Li-Chun

2015-01-01

The purpose of this study was to explore the reading behavior of young proficient Chinese readers at preschool age. Especially, the roles of phonetic skill and Chinese Character recognition in reading comprehension were explored. 10 kindergartens were recruited to participate in the study. Subjects were 72-98 kindergarten children. Instruments…

intelligentCAPTURE 1.0 Adds Tables of Content to Library Catalogues and Improves Retrieval.

ERIC Educational Resources Information Center

Hauer, Manfred; Simedy, Walton

2002-01-01

Describes an online library catalog that was developed for an Austrian scientific library that includes table of contents in addition to the standard bibliographic information in order to increase relevance for searchers. Discusses the technology involved, including OCR (Optical Character Recognition) and automatic indexing techniques; weighted…

EDP Applications to Musical Bibliography: Input Considerations

ERIC Educational Resources Information Center

Robbins, Donald C.

1972-01-01

The application of Electronic Data Processing (EDP) has been a boon in the analysis and bibliographic control of music. However, an extra step of encoding must be undertaken for input of music. The best hope to facilitate musical input is the development of an Optical Character Recognition (OCR) music-reading machine. (29 references) (Author/NH)

Automatic Cataloguing and Searching for Retrospective Data by Use of OCR Text.

ERIC Educational Resources Information Center

Tseng, Yuen-Hsien

2001-01-01

Describes efforts in supporting information retrieval from OCR (optical character recognition) degraded text. Reports on approaches used in an automatic cataloging and searching contest for books in multiple languages, including a vector space retrieval model, an n-gram indexing method, and a weighting scheme; and discusses problems of Asian…

Learner Variables Associated with Reading and Learning in a Hypertext Environment.

ERIC Educational Resources Information Center

Niederhauser, Dale S.; Shapiro, Amy

While many elements like character decoding, word recognition, comprehension, and others remain the same as in learning from traditional text, when learning from hypertext, a number of features that are unique to reading hypertext produce added complexity. It is these features that drive research on hypertext in education. There is a greater…

Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1996-01-01

Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)

Chinese-Mandarin: Basic Course. Volume VII: Lessons 72-79.

ERIC Educational Resources Information Center

Defense Language Inst., Monterey, CA.

This is the seventh of 16 volumes of audiolingual classroom instruction in Mandarin Chinese. The course is designed to train native English speakers to Level 3 Foreign Service Institute proficiency in comprehension and speaking, and to Level 2 proficiency in reading and writing Mandarin. Facility in the use and recognition of Chinese characters is…

Chinese-Mandarin: Basic Course. Volume IX: Lessons 88-95.

ERIC Educational Resources Information Center

Defense Language Inst., Monterey, CA.

This is the ninth of 16 volumes of audiolingual classroom instruction in Mandarin Chinese. The course is designed to train native English speakers to Level 3 Foreign Service Institute proficiency in comprehension and speaking, and to Level 2 proficiency in reading and writing Mandarin. Facility in the use and recognition of Chinese characters is…

Chinese-Mandarin: Basic Course. Volume VIII: Lessons 80-87.

ERIC Educational Resources Information Center

Defense Language Inst., Monterey, CA.

This is the eighth of 16 volumes of audiolingual classroom instruction in Mandarin Chinese. The course is designed to train native English speakers to Level 3 Foreign Service Institute proficiency in comprehension and speaking, and to Level 2 proficiency in reading and writing Mandarin. Facility in the use and recognition of Chinese characters is…

Teaching Braille Letters, Numerals, Punctuation, and Contractions to Sighted Individuals

ERIC Educational Resources Information Center

Putnam, Brittany C.; Tiger, Jeffrey H.

2015-01-01

Braille-character recognition is one of the foundational skills required for teachers of braille. Prior research has evaluated computer programming for teaching braille-to-print letter relations (e.g., Scheithauer & Tiger, 2012). In the current study, we developed a program (the Visual Braille Trainer) to teach not only letters but also…

A usability evaluation of an interactive application for halal products using optical character recognition and augmented reality technologies

NASA Astrophysics Data System (ADS)

Lam, Meng Chun; Nizam, Siti Soleha Muhammad; Arshad, Haslina; A'isyah Ahmad Shukri, Saidatul; Hashim, Nurhazarifah Che; Putra, Haekal Mozzia; Abidin, Rimaniza Zainal

2017-10-01

This article discusses the usability of an interactive application for halal products using Optical Character Recognition (OCR) and Augmented Reality (AR) technologies. Among the problems that have been identified in this study is that consumers have little knowledge about the E-Code. Therefore, users often have doubts about the halal status of the product. Nowadays, the integrity of halal status can be doubtful due to the actions of some irresponsible people spreading false information about a product. Therefore, an application that uses OCR and AR technology developed in this study will help the users to identify the information content of a product by scanning the E-Code label and by scanning the product's brand to know the halal status of the product. In this application, E-Code on the label of a product is scanned using OCR technology to display information about the E-Code. The product's brand is scan using augmented reality technology to display halal status of the product. The findings reveal that users are satisfied with this application and it is useful and easy to use.

Towards Mobile OCR: How To Take a Good Picture of a Document Without Sight.

PubMed

Cutter, Michael; Manduchi, Roberto

The advent of mobile OCR (optical character recognition) applications on regular smartphones holds great promise for enabling blind people to access printed information. Unfortunately, these systems suffer from a problem: in order for OCR output to be meaningful, a well-framed image of the document needs to be taken, something that is difficult to do without sight. This contribution presents an experimental investigation of how blind people position and orient a camera phone while acquiring document images. We developed experimental software to investigate if verbal guidance aids in the acquisition of OCR-readable images without sight. We report on our participant's feedback and performance before and after assistance from our software.

Towards Mobile OCR: How To Take a Good Picture of a Document Without Sight

PubMed Central

Cutter, Michael; Manduchi, Roberto

2015-01-01

The advent of mobile OCR (optical character recognition) applications on regular smartphones holds great promise for enabling blind people to access printed information. Unfortunately, these systems suffer from a problem: in order for OCR output to be meaningful, a well-framed image of the document needs to be taken, something that is difficult to do without sight. This contribution presents an experimental investigation of how blind people position and orient a camera phone while acquiring document images. We developed experimental software to investigate if verbal guidance aids in the acquisition of OCR-readable images without sight. We report on our participant's feedback and performance before and after assistance from our software. PMID:26677461

Deep--deeper--deepest? Encoding strategies and the recognition of human faces.

PubMed

Sporer, S L

1991-03-01

Various encoding strategies that supposedly promote deeper processing of human faces (e.g., character judgments) have led to better recognition than more shallow processing tasks (judging the width of the nose). However, does deeper processing actually lead to an improvement in recognition, or, conversely, does shallow processing lead to a deterioration in performance when compared with naturally employed encoding strategies? Three experiments systematically compared a total of 8 different encoding strategies manipulating depth of processing, amount of elaboration, and self-generation of judgmental categories. All strategies that required a scanning of the whole face were basically equivalent but no better than natural strategy controls. The consistently worst groups were the ones that rated faces along preselected physical dimensions. This can be explained by subjects' lesser task involvement as revealed by manipulation checks.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

An integrated information retrieval and document management system

NASA Technical Reports Server (NTRS)

Coles, L. Stephen; Alvarez, J. Fernando; Chen, James; Chen, William; Cheung, Lai-Mei; Clancy, Susan; Wong, Alexis

1993-01-01

This paper describes the requirements and prototype development for an intelligent document management and information retrieval system that will be capable of handling millions of pages of text or other data. Technologies for scanning, Optical Character Recognition (OCR), magneto-optical storage, and multiplatform retrieval using a Standard Query Language (SQL) will be discussed. The semantic ambiguity inherent in the English language is somewhat compensated-for through the use of coefficients or weighting factors for partial synonyms. Such coefficients are used both for defining structured query trees for routine queries and for establishing long-term interest profiles that can be used on a regular basis to alert individual users to the presence of relevant documents that may have just arrived from an external source, such as a news wire service. Although this attempt at evidential reasoning is limited in comparison with the latest developments in AI Expert Systems technology, it has the advantage of being commercially available.

Image processing for a tactile/vision substitution system using digital CNN.

PubMed

Lin, Chien-Nan; Yu, Sung-Nien; Hu, Jin-Cheng

2006-01-01

In view of the parallel processing and easy implementation properties of CNN, we propose to use digital CNN as the image processor of a tactile/vision substitution system (TVSS). The digital CNN processor is used to execute the wavelet down-sampling filtering and the half-toning operations, aiming to extract important features from the images. A template combination method is used to embed the two image processing functions into a single CNN processor. The digital CNN processor is implemented on an intellectual property (IP) and is implemented on a XILINX VIRTEX II 2000 FPGA board. Experiments are designated to test the capability of the CNN processor in the recognition of characters and human subjects in different environments. The experiments demonstrates impressive results, which proves the proposed digital CNN processor a powerful component in the design of efficient tactile/vision substitution systems for the visually impaired people.

A tool for developing an automatic insect identification system based on wing outlines

PubMed Central

Yang, He-Ping; Ma, Chun-Sen; Wen, Hui; Zhan, Qing-Bin; Wang, Xin-Li

2015-01-01

For some insect groups, wing outline is an important character for species identification. We have constructed a program as the integral part of an automated system to identify insects based on wing outlines (DAIIS). This program includes two main functions: (1) outline digitization and Elliptic Fourier transformation and (2) classifier model training by pattern recognition of support vector machines and model validation. To demonstrate the utility of this program, a sample of 120 owlflies (Neuroptera: Ascalaphidae) was split into training and validation sets. After training, the sample was sorted into seven species using this tool. In five repeated experiments, the mean accuracy for identification of each species ranged from 90% to 98%. The accuracy increased to 99% when the samples were first divided into two groups based on features of their compound eyes. DAIIS can therefore be a useful tool for developing a system of automated insect identification. PMID:26251292

Is There a Downside to Anticipating the Upside? Children's and Adults' Reasoning About How Prior Expectations Shape Future Emotions.

PubMed

Lara, Karen Hjortsvang; Lagattuta, Kristin Hansen; Kramer, Hannah J

2017-11-24

Four- to 10-year-olds and adults (N = 205) responded to vignettes involving three individuals with different expectations (high, low, and no) for a future event. Participants judged characters' pre-outcome emotions, as well as predicted and explained their feelings following three events (positive, attenuated, and negative). Although adults rated high-expectation characters more negatively than low-expectation characters after all outcomes, children shared this intuition starting at 6-7 years for negative outcomes, 8-10 years for attenuated, and never for positive. Comparison to baseline (no expectation) indicated that understanding the costs of high expectations emerges first and remains more robust across age than recognition that low expectations carry benefits. Explanation analyses further clarified this developing awareness about the relation between thoughts and emotions over time. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Rapid Extraction of Lexical Tone Phonology in Chinese Characters: A Visual Mismatch Negativity Study

PubMed Central

Wang, Xiao-Dong; Liu, A-Ping; Wu, Yin-Yuan; Wang, Peng

2013-01-01

Background In alphabetic languages, emerging evidence from behavioral and neuroimaging studies shows the rapid and automatic activation of phonological information in visual word recognition. In the mapping from orthography to phonology, unlike most alphabetic languages in which there is a natural correspondence between the visual and phonological forms, in logographic Chinese, the mapping between visual and phonological forms is rather arbitrary and depends on learning and experience. The issue of whether the phonological information is rapidly and automatically extracted in Chinese characters by the brain has not yet been thoroughly addressed. Methodology/Principal Findings We continuously presented Chinese characters differing in orthography and meaning to adult native Mandarin Chinese speakers to construct a constant varying visual stream. In the stream, most stimuli were homophones of Chinese characters: The phonological features embedded in these visual characters were the same, including consonants, vowels and the lexical tone. Occasionally, the rule of phonology was randomly violated by characters whose phonological features differed in the lexical tone. Conclusions/Significance We showed that the violation of the lexical tone phonology evoked an early, robust visual response, as revealed by whole-head electrical recordings of the visual mismatch negativity (vMMN), indicating the rapid extraction of phonological information embedded in Chinese characters. Source analysis revealed that the vMMN was involved in neural activations of the visual cortex, suggesting that the visual sensory memory is sensitive to phonological information embedded in visual words at an early processing stage. PMID:23437235

Seed morphology and anatomy and its utility in recognizing subfamilies and tribes of Zingiberaceae.

PubMed

Benedict, John C; Smith, Selena Y; Collinson, Margaret E; Leong-Škorničková, Jana; Specht, Chelsea D; Marone, Federica; Xiao, Xianghui; Parkinson, Dilworth Y

2015-11-01

Recent phylogenetic analyses based on molecular data suggested that the monocot family Zingiberaceae be separated into four subfamilies and four tribes. Robust morphological characters to support these clades are lacking. Seeds were analyzed in a phylogenetic context to test independently the circumscription of clades and to better understand evolution of seed characters within Zingiberaceae. Seventy-five species from three of the four subfamilies were analyzed using synchrotron based x-ray tomographic microscopy (SRXTM) and scored for 39 morphoanatomical characters. Zingiberaceae seeds are some of the most structurally complex seeds in angiosperms. No single seed character was found to distinguish each subfamily, but combinations of characters were found to differentiate between the subfamilies. Recognition of the tribes based on seeds was possible for Globbeae, but not for Alpinieae, Riedelieae, or Zingibereae, due to considerable variation. SRXTM is an excellent, nondestructive tool to capture morphoanatomical variation of seeds and allows for the study of taxa with limited material available. Alpinioideae, Siphonochiloideae, Tamijioideae, and Zingiberoideae are well supported based on both molecular and morphological data, including multiple seed characters. Globbeae are well supported as a distinctive tribe within the Zingiberoideae, but no other tribe could be differentiated using seeds due to considerable homoplasy when compared with currently accepted relationships based on molecular data. Novel seed characters suggest tribal affinities for two currently unplaced Zingiberaceae taxa: Siliquamomum may be related to Riedelieae and Monolophus to Zingibereae, but further work is needed before formal revision of the family. © 2015 Botanical Society of America.

Electrophysiological Correlates of Familiarity and Recollection in Associative Recognition: Contributions of Perceptual and Conceptual Processing to Unitization

PubMed Central

Li, Bingcan; Mao, Xinrui; Wang, Yujuan; Guo, Chunyan

2017-01-01

It is generally accepted that associative recognition memory is supported by recollection. In addition, recent research indicates that familiarity can support associative memory, especially when two items are unitized into a single item. Both perceptual and conceptual manipulations can be used to unitize items, but few studies have compared these two methods of unitization directly. In the present study, we investigated the effects of familiarity and recollection on successful retrieval of items that were unitized perceptually or conceptually. Participants were instructed to remember either a Chinese two-character compound or unrelated word-pairs, which were presented simultaneously or sequentially. Participants were then asked to recognize whether word-pairs were intact or rearranged. Event-related potential (ERP) recordings were performed during the recognition phase of the study. Two-character compounds were better discriminated than unrelated word-pairs and simultaneous presentation was found to elicit better discrimination than sequential presentation for unrelated word-pairs only. ERP recordings indicated that the early intact/rearranged effects (FN400), typically associated with familiarity, were elicited in compound word-pairs with both simultaneous and sequential presentation, and in simultaneously presented unrelated word-pairs, but not in sequentially presented unrelated word-pairs. In contrast, the late positive complex (LPC) effects associated with recollection were elicited in all four conditions. Together, these results indicate that while the engagement of familiarity in associative recognition is affected by both perceptual and conceptual unitization, conceptual unitization promotes a higher level of unitization (LOU). In addition, the engagement of recollection was not affected by unitized manipulations. It should be noted, however, that due to experimental design, the effects presented here may be due to semantic rather than episodic memory and future studies should take this into consideration when manipulating rearranged pairs. PMID:28400723

Character complexity and redundancy in writing systems over human history.

PubMed

Changizi, Mark A; Shimojo, Shinsuke

2005-02-07

A writing system is a visual notation system wherein a repertoire of marks, or strokes, is used to build a repertoire of characters. Are there any commonalities across writing systems concerning the rules governing how strokes combine into characters; commonalities that might help us identify selection pressures on the development of written language? In an effort to answer this question we examined how strokes combine to make characters in more than 100 writing systems over human history, ranging from about 10 to 200 characters,and including numerals, abjads, abugidas, alphabets and syllabaries from five major taxa: Ancient Near-Eastern, European, Middle Eastern, South Asian, Southeast Asian. We discovered underlying similarities in two fundamental respects. (i) The number of strokes per characters is approximately three, independent of the number of characters in the writing system; numeral systems are the exception, having on average only two strokes per character. (ii) Characters are ca. 50% redundant, independent of writing system size; intuitively, this means that acharacter's identity can be determined even when half of its strokes are removed. Because writing systems are under selective pressure to have characters that are easy for the visual system to recognize and for the motor system to write, these fundamental commonalities may be a fingerprint of mechanisms underlying the visuo-motor system.

Character complexity and redundancy in writing systems over human history

PubMed Central

Changizi, Mark A.; Shimojo, Shinsuke

2005-01-01

A writing system is a visual notation system wherein a repertoire of marks, or strokes, is used to build a repertoire of characters. Are there any commonalities across writing systems concerning the rules governing how strokes combine into characters; commonalities that might help us identify selection pressures on the development of written language? In an effort to answer this question we examined how strokes combine to make characters in more than 100 writing systems over human history, ranging from about 10 to 200 characters, and including numerals, abjads, abugidas, alphabets and syllabaries from five major taxa: Ancient Near-Eastern, European, Middle Eastern, South Asian, Southeast Asian. We discovered underlying similarities in two fundamental respects.The number of strokes per characters is approximately three, independent of the number of characters in the writing system; numeral systems are the exception, having on average only two strokes per character.Characters are ca. 50% redundant, independent of writing system size; intuitively, this means that a character’s identity can be determined even when half of its strokes are removed.Because writing systems are under selective pressure to have characters that are easy for the visual system to recognize and for the motor system to write, these fundamental commonalities may be a fingerprint of mechanisms underlying the visuo–motor system. PMID:15705551

Identifying hidden rate changes in the evolution of a binary morphological character: the evolution of plant habit in campanulid angiosperms.

PubMed

Beaulieu, Jeremy M; O'Meara, Brian C; Donoghue, Michael J

2013-09-01

The growth of phylogenetic trees in scope and in size is promising from the standpoint of understanding a wide variety of evolutionary patterns and processes. With trees comprised of larger, older, and globally distributed clades, it is likely that the lability of a binary character will differ significantly among lineages, which could lead to errors in estimating transition rates and the associated inference of ancestral states. Here we develop and implement a new method for identifying different rates of evolution in a binary character along different branches of a phylogeny. We illustrate this approach by exploring the evolution of growth habit in Campanulidae, a flowering plant clade containing some 35,000 species. The distribution of woody versus herbaceous species calls into question the use of traditional models of binary character evolution. The recognition and accommodation of changes in the rate of growth form evolution in different lineages demonstrates, for the first time, a robust picture of growth form evolution across a very large, very old, and very widespread flowering plant clade.

Foveal splitting causes differential processing of Chinese orthography in the male and female brain.

PubMed

Hsiao, Janet Hui-Wen; Shillcock, Richard

2005-10-01

Chinese characters contain separate phonetic and semantic radicals. A dominant character type exists in which the semantic radical is on the left and the phonetic radical on the right; an opposite, minority structure also exists, with the semantic radical on the right and the phonetic radical on the left. We show that, when asked to pronounce isolated tokens of these two character types, males responded significantly faster when the phonetic information was on the right, whereas females showed a non-significant tendency in the opposite direction. Recent research on foveal structure and reading suggests that the two halves of a centrally fixated character are initially processed in different hemispheres. The male brain typically relies more on the left hemisphere for phonological processing compared with the female brain, causing this gender difference to emerge. This interaction is predicted by an implemented computational model. This study supports the existence of a gender difference in phonological processing, and shows that the effects of foveal splitting in reading extend far enough into word recognition to interact with the gender of the reader in a naturalistic reading task.

Attentional focus affects how events are segmented and updated in narrative reading.

PubMed

Bailey, Heather R; Kurby, Christopher A; Sargent, Jesse Q; Zacks, Jeffrey M

2017-08-01

Readers generate situation models representing described events, but the nature of these representations may differ depending on the reading goals. We assessed whether instructions to pay attention to different situational dimensions affect how individuals structure their situation models (Exp. 1) and how they update these models when situations change (Exp. 2). In Experiment 1, participants read and segmented narrative texts into events. Some readers were oriented to pay specific attention to characters or space. Sentences containing character or spatial-location changes were perceived as event boundaries-particularly if the reader was oriented to characters or space, respectively. In Experiment 2, participants read narratives and responded to recognition probes throughout the texts. Readers who were oriented to the spatial dimension were more likely to update their situation models at spatial changes; all readers tracked the character dimension. The results from both experiments indicated that attention to individual situational dimensions influences how readers segment and update their situation models. More broadly, the results provide evidence for a global situation model updating mechanism that serves to set up new models at important narrative changes.

A Chinese Character Teaching System Using Structure Theory and Morphing Technology

PubMed Central

Sun, Linjia; Liu, Min; Hu, Jiajia; Liang, Xiaohui

2014-01-01

This paper proposes a Chinese character teaching system by using the Chinese character structure theory and the 2D contour morphing technology. This system, including the offline phase and the online phase, automatically generates animation for the same Chinese character from different writing stages to intuitively show the evolution of shape and topology in the process of Chinese characters teaching. The offline phase builds the component models database for the same script and the components correspondence database for different scripts. Given two or several different scripts of the same Chinese character, the online phase firstly divides the Chinese characters into components by using the process of Chinese character parsing, and then generates the evolution animation by using the process of Chinese character morphing. Finally, two writing stages of Chinese characters, i.e., seal script and clerical script, are used in experiment to show the ability of the system. The result of the user experience study shows that the system can successfully guide students to improve the learning of Chinese characters. And the users agree that the system is interesting and can motivate them to learn. PMID:24978171

Prosodic expectations in silent reading: ERP evidence from rhyme scheme and semantic congruence in classic Chinese poems.

PubMed

Chen, Qingrong; Zhang, Jingjing; Xu, Xiaodong; Scheepers, Christoph; Yang, Yiming; Tanenhaus, Michael K

2016-09-01

In an ERP study, classic Chinese poems with a well-known rhyme scheme were used to generate an expectation of a rhyme in the absence of an expectation for a specific character. Critical characters were either consistent or inconsistent with the expected rhyme scheme and semantically congruent or incongruent with the content of the poem. These stimuli allowed us to examine whether a top-down rhyme scheme expectation would affect relatively early components of the ERP associated with character-to-sound mapping (P200) and lexically-mediated semantic processing (N400). The ERP data revealed that rhyme scheme congruence, but not semantic congruence modulated the P200: rhyme-incongruent characters elicited a P200 effect across the head demonstrating that top-down expectations influence early phonological coding of the character before lexical-semantic processing. Rhyme scheme incongruence also produced a right-lateralized N400-like effect. Moreover, compared to semantically congruous poems, semantically incongruous poems produced a larger N400 response only when the character was consistent with the expected rhyme scheme. The results suggest that top-down prosodic expectations can modulate early phonological processing in visual word recognition, indicating that prosodic expectations might play an important role in silent reading. They also suggest that semantic processing is influenced by general knowledge of text genre. Copyright © 2016 Elsevier B.V. All rights reserved.

Brand logo recognition by children aged 3 to 6 years. Mickey Mouse and Old Joe the Camel.

PubMed

Fischer, P M; Schwartz, M P; Richards, J W; Goldstein, A O; Rojas, T H

1991-12-11

Little is known about the influence of advertising on very young children. We, therefore, measured product logo recognition by subjects aged 3 to 6 years. Children were instructed to match logos with one of 12 products pictured on a game board. Twenty-two logos were tested, including those representing children's products, adult products, and those for two popular cigarette brands (Camel and Marlboro). Preschools in Augusta and Atlanta, Ga. A convenience sample of 229 children attending preschool. The children demonstrated high rates of logo recognition. When analyzed by product category, the level of recognition of cigarette logos was intermediate between children's and adult products. The recognition rates of The Disney Channel logo and Old Joe (the cartoon character promoting Camel cigarettes) were highest in their respective product categories. Recognition rates increased with age. Approximately 30% of 3-year-old children correctly matched Old Joe with a picture of a cigarette compared with 91.3% of 6-year-old children. Very young children see, understand, and remember advertising. Given the serious health consequences of smoking, the exposure of children to environmental tobacco advertising may represent an important health risk and should be studied further.

Technologies for developing an advanced intelligent ATM with self-defence capabilities

NASA Astrophysics Data System (ADS)

Sako, Hiroshi

2010-01-01

We have developed several technologies for protecting automated teller machines. These technologies are based mainly on pattern recognition and are used to implement various self-defence functions. They include (i) banknote recognition and information retrieval for preventing machines from accepting counterfeit and damaged banknotes and for retrieving information about detected counterfeits from a relational database, (ii) form processing and character recognition for preventing machines from accepting remittance forms without due dates and/or insufficient payment, (iii) person identification to prevent machines from transacting with non-customers, and (iv) object recognition to guard machines against foreign objects such as spy cams that might be surreptitiously attached to them and to protect users against someone attempting to peek at their user information such as their personal identification number. The person identification technology has been implemented in most ATMs in Japan, and field tests have demonstrated that the banknote recognition technology can recognise more then 200 types of banknote from 30 different countries. We are developing an "advanced intelligent ATM" that incorporates all of these technologies.

Sample data processing in an additive and reproducible taxonomic workflow by using character data persistently linked to preserved individual specimens

PubMed Central

Kilian, Norbert; Henning, Tilo; Plitzner, Patrick; Müller, Andreas; Güntsch, Anton; Stöver, Ben C.; Müller, Kai F.; Berendsohn, Walter G.; Borsch, Thomas

2015-01-01

We present the model and implementation of a workflow that blazes a trail in systematic biology for the re-usability of character data (data on any kind of characters of pheno- and genotypes of organisms) and their additivity from specimen to taxon level. We take into account that any taxon characterization is based on a limited set of sampled individuals and characters, and that consequently any new individual and any new character may affect the recognition of biological entities and/or the subsequent delimitation and characterization of a taxon. Taxon concepts thus frequently change during the knowledge generation process in systematic biology. Structured character data are therefore not only needed for the knowledge generation process but also for easily adapting characterizations of taxa. We aim to facilitate the construction and reproducibility of taxon characterizations from structured character data of changing sample sets by establishing a stable and unambiguous association between each sampled individual and the data processed from it. Our workflow implementation uses the European Distributed Institute of Taxonomy Platform, a comprehensive taxonomic data management and publication environment to: (i) establish a reproducible connection between sampled individuals and all samples derived from them; (ii) stably link sample-based character data with the metadata of the respective samples; (iii) record and store structured specimen-based character data in formats allowing data exchange; (iv) reversibly assign sample metadata and character datasets to taxa in an editable classification and display them and (v) organize data exchange via standard exchange formats and enable the link between the character datasets and samples in research collections, ensuring high visibility and instant re-usability of the data. The workflow implemented will contribute to organizing the interface between phylogenetic analysis and revisionary taxonomic or monographic work. Database URL: http://campanula.e-taxonomy.net/ PMID:26424081

Effects of licensed characters on children's taste and snack preferences in Guatemala, a low/middle income country.

PubMed

Letona, P; Chacon, V; Roberto, C; Barnoya, J

2014-11-01

Marketing of high-energy, low-nutrient foods is one of the contributing factors to the obesity-promoting environment. Licensed characters are typically used to market these foods to children because they increase brand recognition and sales, and data suggest that they affect the taste and snack preferences of children in high-income countries, but it has not yet been explored in low/middle income countries (LMICs). We sought to examine how licensed characters on food packaging influence children's taste and snack preferences in Guatemala, a LMIC. One hundred twenty-one children (mean ± s.d. age, 7.4 ± 1.9 years) from four (two preschool and two elementary) public schools in Guatemala tasted three food types: potato chips, crackers and carrots. Each was presented in two identical packages, except that one had a licensed character and the other did not. Children tasted the foods (six total) in each package and answered whether they tasted the same or one tasted better. Snack preference was also evaluated. Children were significantly (P<0.001) more likely to prefer the taste of the foods inside the package with the licensed character compared with the one with no character (mean ± s.d., 0.24 ± 0.54). Most (66%) chose the food in the package with the character for a snack. Younger children (P < 0.001) were more likely to prefer the taste of the food inside the package with the character. Licensed characters on food packaging influence Guatemalan children's taste and snack preferences. Given that these characters are typically used to promote high-energy, low-nutrient foods, their influence could contribute toward overconsumption of these foods and consequently increased risk of obesity in Guatemalan children. Therefore, public health advocates, in Guatemala and elsewhere, might explore restricting the use of licensed characters on food packaging as a public health strategy.

Error-Correcting Parsing for Syntactic Pattern Recognition

DTIC Science & Technology

1977-08-01

1971. 55. Slromoney, G., Slromoney, R., and K. Krlthlvasan, "Abstract Families of Matrices and Picture Langauges," Computer Graphic and Image...T112 111X1 121 Tine USLO FOR LINXirjG A THtt .186 SEC "INPUT CHARACTER IS A DISTANCE PORN N0*flAL A IS_ 3 TINE USED FOX PARSING S.l&l SEC

IFLA Section of Libraries for the Blind. Expert Meeting, 1984. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations, The Hague (Netherlands).

Papers on library services and developments in reading materials for the blind, which were presented at the 1984 Expert Meeting of the IFLA Section of Libraries for the Blind include: (1) "Teaching Map Concepts to the Blind" (R. B. Horsfall and B. Cox, Canada); (2) "Optical Character Recognition 'Reading' for Computerized Braille Production"…

The Compensatory Effectiveness of the Quicktionary Reading Pen II on the Reading Comprehension of Students with Learning Disabilities

ERIC Educational Resources Information Center

Higgins, Eleanor L.; Raskind, Marshall H.

2005-01-01

The study investigated the compensatory effectiveness of the Quicktionary Reading Pen II (the Reading Pen), a portable device with miniaturized optical character recognition and speech synthesis capabilities. Thirty participants with reading disabilities aged 10-18 were trained on the operation of the technology and given two weeks to practice…

Arabic Optical Character Recognition (OCR) Evaluation in Order to Develop a Post-OCR Module

DTIC Science & Technology

2011-09-01

handwritten, and many more have some handwriting in the margins. Some images are blurred or faded to the point of illegibility. Others are mostly or...it is to English, because Arabic has more features such as agreement. We say that Arabic is more “morphologically rich” than English. We intend to

The Role of the Ventral and Dorsal Pathways in Reading Chinese Characters and English Words

ERIC Educational Resources Information Center

Sun, Yafeng; Yang, Yanhui; Desroches, Amy S.; Liu, Li; Peng, Danling

2011-01-01

Previous literature in alphabetic languages suggests that the occipital-temporal region (the ventral pathway) is specialized for automatic parallel word recognition, whereas the parietal region (the dorsal pathway) is specialized for serial letter-by-letter reading (and). However, few studies have directly examined the role of the ventral and…

Optimizing Learning of Scientific Category Knowledge in the Classroom: The Case of Plant Identification

ERIC Educational Resources Information Center

Kirchoff, Bruce K.; Delaney, Peter F.; Horton, Meg; Dellinger-Johnston, Rebecca

2014-01-01

Learning to identify organisms is extraordinarily difficult, yet trained field biologists can quickly and easily identify organisms at a glance. They do this without recourse to the use of traditional characters or identification devices. Achieving this type of recognition accuracy is a goal of many courses in plant systematics. Teaching plant…

[Design and synthesis of imine compound for metal cation logical gates recognition and setup of double-control fluorescent molecule switch].

PubMed

Huang, Tao; Zhu, Yu-lian; Dai, Xue-qin; Zhang, Qi; Huang, Yan

2011-07-01

The Schiff base's reduced product N,N-bis(4-methoxybenzyl) ethane-1,2-diamine, which was used as a receptor L, was designed and synthesized for the first time in the present article. It was found that Cu2+ and Fe3+ could quench L in fluorescence observably and Zn2+ and Cd2+ could enhance L remarkably. So the two pair metal cation could set up "OR" logical gate relation with the receptor molecule L, then a logical recognition system be formed. The data of resolved ZnL's single crystal indicated that ZnL belonged to monoclinic (CCDC No. 747994). Integrated spectrum instrument was used to characterize the structure of its alike series of complex compound. According to ZnL's excellent fluorescence character and the ability to exchange with contiguous metal cation, ZnZ+/ZnL/Co2+, Zn2+/ZnL/Nit+ fluorescent molecule switch was designed. It is hoped that the work above could be positive for the development of molecule computer, bio-intellectualized inspection technology (therapy) and instrument.

Emotion recognition from EEG using higher order crossings.

PubMed

Petrantonakis, Panagiotis C; Hadjileontiadis, Leontios J

2010-03-01

Electroencephalogram (EEG)-based emotion recognition is a relatively new field in the affective computing area with challenging issues regarding the induction of the emotional states and the extraction of the features in order to achieve optimum classification performance. In this paper, a novel emotion evocation and EEG-based feature extraction technique is presented. In particular, the mirror neuron system concept was adapted to efficiently foster emotion induction by the process of imitation. In addition, higher order crossings (HOC) analysis was employed for the feature extraction scheme and a robust classification method, namely HOC-emotion classifier (HOC-EC), was implemented testing four different classifiers [quadratic discriminant analysis (QDA), k-nearest neighbor, Mahalanobis distance, and support vector machines (SVMs)], in order to accomplish efficient emotion recognition. Through a series of facial expression image projection, EEG data have been collected by 16 healthy subjects using only 3 EEG channels, namely Fp1, Fp2, and a bipolar channel of F3 and F4 positions according to 10-20 system. Two scenarios were examined using EEG data from a single-channel and from combined-channels, respectively. Compared with other feature extraction methods, HOC-EC appears to outperform them, achieving a 62.3% (using QDA) and 83.33% (using SVM) classification accuracy for the single-channel and combined-channel cases, respectively, differentiating among the six basic emotions, i.e., happiness, surprise, anger, fear, disgust, and sadness. As the emotion class-set reduces its dimension, the HOC-EC converges toward maximum classification rate (100% for five or less emotions), justifying the efficiency of the proposed approach. This could facilitate the integration of HOC-EC in human machine interfaces, such as pervasive healthcare systems, enhancing their affective character and providing information about the user's emotional status (e.g., identifying user's emotion experiences, recurring affective states, time-dependent emotional trends).

Character: A Multifaceted Developmental System

ERIC Educational Resources Information Center

Nucci, Larry

2017-01-01

Character is a developmental system embedded within the self-system. This Relational Developmental Systems (RDS) view is in juxtaposition with virtue theory and accounts of character in terms of moral identity. The character system includes 4 components 3 of which: basic moral cognition (as described within domain theory); other regarding; and…

The DSFPN, a new neural network for optical character recognition.

PubMed

Morns, L P; Dlay, S S

1999-01-01

A new type of neural network for recognition tasks is presented in this paper. The network, called the dynamic supervised forward-propagation network (DSFPN), is based on the forward only version of the counterpropagation network (CPN). The DSFPN, trains using a supervised algorithm and can grow dynamically during training, allowing subclasses in the training data to be learnt in an unsupervised manner. It is shown to train in times comparable to the CPN while giving better classification accuracies than the popular backpropagation network. Both Fourier descriptors and wavelet descriptors are used for image preprocessing and the wavelets are proven to give a far better performance.

Binary zone-plate array for a parallel joint transform correlator applied to face recognition.

PubMed

Kodate, K; Hashimoto, A; Thapliya, R

1999-05-10

Taking advantage of small aberrations, high efficiency, and compactness, we developed a new, to our knowledge, design procedure for a binary zone-plate array (BZPA) and applied it to a parallel joint transform correlator for the recognition of the human face. Pairs of reference and unknown images of faces are displayed on a liquid-crystal spatial light modulator (SLM), Fourier transformed by the BZPA, intensity recorded on an optically addressable SLM, and inversely Fourier transformed to obtain correlation signals. Consideration of the bandwidth allows the relations among the channel number, the numerical aperture of the zone plates, and the pattern size to be determined. Experimentally a five-channel parallel correlator was implemented and tested successfully with a 100-person database. The design and the fabrication of a 20-channel BZPA for phonetic character recognition are also included.

Constructing Stylish Characters on Computer Graphics Systems.

ERIC Educational Resources Information Center

Goldman, Gary S.

1980-01-01

Computer graphics systems typically produce a single, machine-like character font. At most, these systems enable the user to (1) alter the aspect ratio (height-to-width ratio) of the characters, (2) specify a transformation matrix to slant the characters, and (3) define a virtual pen table to change the lineweight of the plotted characters.…

Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

PubMed Central

Vajda, Szilárd; Rangoni, Yves; Cecotti, Hubert

2015-01-01

For training supervised classifiers to recognize different patterns, large data collections with accurate labels are necessary. In this paper, we propose a generic, semi-automatic labeling technique for large handwritten character collections. In order to speed up the creation of a large scale ground truth, the method combines unsupervised clustering and minimal expert knowledge. To exploit the potential discriminant complementarities across features, each character is projected into five different feature spaces. After clustering the images in each feature space, the human expert labels the cluster centers. Each data point inherits the label of its cluster’s center. A majority (or unanimity) vote decides the label of each character image. The amount of human involvement (labeling) is strictly controlled by the number of clusters – produced by the chosen clustering approach. To test the efficiency of the proposed approach, we have compared, and evaluated three state-of-the art clustering methods (k-means, self-organizing maps, and growing neural gas) on the MNIST digit data set, and a Lampung Indonesian character data set, respectively. Considering a k-nn classifier, we show that labeling manually only 1.3% (MNIST), and 3.2% (Lampung) of the training data, provides the same range of performance than a completely labeled data set would. PMID:25870463

Mobile-based text recognition from water quality devices

NASA Astrophysics Data System (ADS)

Dhakal, Shanti; Rahnemoonfar, Maryam

2015-03-01

Measuring water quality of bays, estuaries, and gulfs is a complicated and time-consuming process. YSI Sonde is an instrument used to measure water quality parameters such as pH, temperature, salinity, and dissolved oxygen. This instrument is taken to water bodies in a boat trip and researchers note down different parameters displayed by the instrument's display monitor. In this project, a mobile application is developed for Android platform that allows a user to take a picture of the YSI Sonde monitor, extract text from the image and store it in a file on the phone. The image captured by the application is first processed to remove perspective distortion. Probabilistic Hough line transform is used to identify lines in the image and the corner of the image is then obtained by determining the intersection of the detected horizontal and vertical lines. The image is warped using the perspective transformation matrix, obtained from the corner points of the source image and the destination image, hence, removing the perspective distortion. Mathematical morphology operation, black-hat is used to correct the shading of the image. The image is binarized using Otsu's binarization technique and is then passed to the Optical Character Recognition (OCR) software for character recognition. The extracted information is stored in a file on the phone and can be retrieved later for analysis. The algorithm was tested on 60 different images of YSI Sonde with different perspective features and shading. Experimental results, in comparison to ground-truth results, demonstrate the effectiveness of the proposed method.

Automated Car Park Management System

NASA Astrophysics Data System (ADS)

Fabros, J. P.; Tabañag, D.; Espra, A.; Gerasta, O. J.

2015-06-01

This study aims to develop a prototype for an Automated Car Park Management System that will increase the quality of service of parking lots through the integration of a smart system that assists motorist in finding vacant parking lot. The research was based on implementing an operating system and a monitoring system for parking system without the use of manpower. This will include Parking Guidance and Information System concept which will efficiently assist motorists and ensures the safety of the vehicles and the valuables inside the vehicle. For monitoring, Optical Character Recognition was employed to monitor and put into list all the cars entering the parking area. All parking events in this system are visible via MATLAB GUI which contain time-in, time-out, time consumed information and also the lot number where the car parks. To put into reality, this system has a payment method, and it comes via a coin slot operation to control the exit gate. The Automated Car Park Management System was successfully built by utilizing microcontrollers specifically one PIC18f4550 and two PIC16F84s and one PIC16F628A.

End-to-End ASR-Free Keyword Search From Speech

NASA Astrophysics Data System (ADS)

Audhkhasi, Kartik; Rosenberg, Andrew; Sethy, Abhinav; Ramabhadran, Bhuvana; Kingsbury, Brian

2017-12-01

End-to-end (E2E) systems have achieved competitive results compared to conventional hybrid hidden Markov model (HMM)-deep neural network based automatic speech recognition (ASR) systems. Such E2E systems are attractive due to the lack of dependence on alignments between input acoustic and output grapheme or HMM state sequence during training. This paper explores the design of an ASR-free end-to-end system for text query-based keyword search (KWS) from speech trained with minimal supervision. Our E2E KWS system consists of three sub-systems. The first sub-system is a recurrent neural network (RNN)-based acoustic auto-encoder trained to reconstruct the audio through a finite-dimensional representation. The second sub-system is a character-level RNN language model using embeddings learned from a convolutional neural network. Since the acoustic and text query embeddings occupy different representation spaces, they are input to a third feed-forward neural network that predicts whether the query occurs in the acoustic utterance or not. This E2E ASR-free KWS system performs respectably despite lacking a conventional ASR system and trains much faster.

Acceleration of spiking neural network based pattern recognition on NVIDIA graphics processors.

PubMed

Han, Bing; Taha, Tarek M

2010-04-01

There is currently a strong push in the research community to develop biological scale implementations of neuron based vision models. Systems at this scale are computationally demanding and generally utilize more accurate neuron models, such as the Izhikevich and the Hodgkin-Huxley models, in favor of the more popular integrate and fire model. We examine the feasibility of using graphics processing units (GPUs) to accelerate a spiking neural network based character recognition network to enable such large scale systems. Two versions of the network utilizing the Izhikevich and Hodgkin-Huxley models are implemented. Three NVIDIA general-purpose (GP) GPU platforms are examined, including the GeForce 9800 GX2, the Tesla C1060, and the Tesla S1070. Our results show that the GPGPUs can provide significant speedup over conventional processors. In particular, the fastest GPGPU utilized, the Tesla S1070, provided a speedup of 5.6 and 84.4 over highly optimized implementations on the fastest central processing unit (CPU) tested, a quadcore 2.67 GHz Xeon processor, for the Izhikevich and the Hodgkin-Huxley models, respectively. The CPU implementation utilized all four cores and the vector data parallelism offered by the processor. The results indicate that GPUs are well suited for this application domain.

The Evolution of Invasiveness in Garden Ants

PubMed Central

Cremer, Sylvia; Ugelvig, Line V.; Drijfhout, Falko P.; Schlick-Steiner, Birgit C.; Steiner, Florian M.; Seifert, Bernhard; Hughes, David P.; Schulz, Andreas; Petersen, Klaus S.; Konrad, Heino; Stauffer, Christian; Kiran, Kadri; Espadaler, Xavier; d'Ettorre, Patrizia; Aktaç, Nihat; Eilenberg, Jørgen; Jones, Graeme R.; Nash, David R.; Pedersen, Jes S.; Boomsma, Jacobus J.

2008-01-01

It is unclear why some species become successful invaders whilst others fail, and whether invasive success depends on pre-adaptations already present in the native range or on characters evolving de-novo after introduction. Ants are among the worst invasive pests, with Lasius neglectus and its rapid spread through Europe and Asia as the most recent example of a pest ant that may become a global problem. Here, we present the first integrated study on behavior, morphology, population genetics, chemical recognition and parasite load of L. neglectus and its non-invasive sister species L. turcicus. We find that L. neglectus expresses the same supercolonial syndrome as other invasive ants, a social system that is characterized by mating without dispersal and large networks of cooperating nests rather than smaller mutually hostile colonies. We conclude that the invasive success of L. neglectus relies on a combination of parasite-release following introduction and pre-adaptations in mating system, body-size, queen number and recognition efficiency that evolved long before introduction. Our results challenge the notion that supercolonial organization is an inevitable consequence of low genetic variation for chemical recognition cues in small invasive founder populations. We infer that low variation and limited volatility in cuticular hydrocarbon profiles already existed in the native range in combination with low dispersal and a highly viscous population structure. Human transport to relatively disturbed urban areas thus became the decisive factor to induce parasite release, a well established general promoter of invasiveness in non-social animals and plants, but understudied in invasive social insects. PMID:19050762

Integrating Character Education Model With Spiral System In Chemistry Subject

NASA Astrophysics Data System (ADS)

Hartutik; Rusdarti; Sumaryanto; Supartono

2017-04-01

Integrating character education is the responsibility of all subject teachers including chemistry teacher. The integration of character education is just administrative requirements so that the character changes are not measurable. The research objective 1) describing the actual conditions giving character education, 2) mapping the character integration of chemistry syllabus with a spiral system, and 3) producing syllabus and guide system integrating character education in chemistry lessons. Of the eighteen value character, each character is mapped to the material chemistry value concepts of class X and repeated the system in class XI and class XII. Spiral system integration means integrating the character values of chemistry subjects in steps from class X to XII repeatedly at different depth levels. Besides developing the syllabus, also made the integration of characters in a learning guide. This research was designed with research and development [3] with the scope of 20 chemistry teachers in Semarang. The focus of the activities is the existence of the current character study, mapping the character values in the syllabus, and assessment of the integration guides of character education. The validity test of Syllabus and Lesson Plans by experts in FGD. The data were taken with questionnaire and interviews, then processed by descriptive analysis. The result shows 1) The factual condition, in general, the teachers designed learning one-time face-to-face with the integration of more than four characters so that behaviour changes and depth of character is poorly controlled, 2) Mapping each character values focused in the syllabus. Meaning, on one or two basic competence in four or five times, face to face, enough integrated with the value of one character. In this way, there are more noticeable changes in students behaviour. Guidance is needed to facilitate the integration of character education for teachers integrating systems. Product syllabus and guidelines validated by experts and the syllabus results averaging 4.37; guidebooks integrating character education in chemistry learning 4.36 with a maximum score of 5. Thus the device is declared valid. Through focus group discussions, each expert gave input for the improvement of learning modules of character education.

Computer vision cracks the leaf code

PubMed Central

Wilf, Peter; Zhang, Shengping; Chikkerur, Sharat; Little, Stefan A.; Wing, Scott L.; Serre, Thomas

2016-01-01

Understanding the extremely variable, complex shape and venation characters of angiosperm leaves is one of the most challenging problems in botany. Machine learning offers opportunities to analyze large numbers of specimens, to discover novel leaf features of angiosperm clades that may have phylogenetic significance, and to use those characters to classify unknowns. Previous computer vision approaches have primarily focused on leaf identification at the species level. It remains an open question whether learning and classification are possible among major evolutionary groups such as families and orders, which usually contain hundreds to thousands of species each and exhibit many times the foliar variation of individual species. Here, we tested whether a computer vision algorithm could use a database of 7,597 leaf images from 2,001 genera to learn features of botanical families and orders, then classify novel images. The images are of cleared leaves, specimens that are chemically bleached, then stained to reveal venation. Machine learning was used to learn a codebook of visual elements representing leaf shape and venation patterns. The resulting automated system learned to classify images into families and orders with a success rate many times greater than chance. Of direct botanical interest, the responses of diagnostic features can be visualized on leaf images as heat maps, which are likely to prompt recognition and evolutionary interpretation of a wealth of novel morphological characters. With assistance from computer vision, leaves are poised to make numerous new contributions to systematic and paleobotanical studies. PMID:26951664

The Development of Appreciation Learning Model of Indonesia Literature Based Critical Discourse Analysis to Improve the Students' Critical Thinking Skill

ERIC Educational Resources Information Center

Mustofa; Yuwana, H. Setya

2016-01-01

Learning literature should be taken to instill recognition, familiarity and enjoyment of literature as a vehicle for character education. Learning literature must be packaged properly so that students interested in compose competence by developing literature learning models. In an effort to assist students in understanding the success of…

Digitization and the Creation of Virtual Libraries: The Princeton University Image Card Catalog--Reaping the Benefits of Imaging.

ERIC Educational Resources Information Center

Henthorne, Eileen

1995-01-01

Describes a project at the Princeton University libraries that converted the pre-1981 public card catalog, using digital imaging and optical character recognition technology, to fully tagged and indexed records of text in MARC format that are available on an online database and will be added to the online catalog. (LRW)

Kurzweil Reading Machine: A Partial Evaluation of Its Optical Character Recognition Error Rate.

ERIC Educational Resources Information Center

Goodrich, Gregory L.; And Others

1979-01-01

A study designed to assess the ability of the Kurzweil reading machine (a speech reading device for the visually handicapped) to read three different type styles produced by five different means indicated that the machines tested had different error rates depending upon the means of producing the copy and upon the type style used. (Author/CL)

26 CFR 1.737-1 - Recognition of precontribution gain.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Property A1 and Property A2 is long-term, U.S.-source capital gain or loss. The character of gain on Property A3 is long-term, foreign-source capital gain. B contributes Property B, nondepreciable real... long-term, U.S.-source capital gain ($10,000 gain on Property A1 and $8,000 loss on Property A2) and $1...

26 CFR 1.367(a)-6T - Transfer of foreign branch with previously deducted losses (temporary).

Code of Federal Regulations, 2012 CFR

2012-04-01

... recaptured by the recognition of the gain realized on the transfer. Paragraph (c) of this section sets forth rules concerning the character of, and limitations on, the gain required to be recognized. Paragraph (d... of gain required—(1) In general. If a U.S. person transfers any assets of a foreign branch to a...

26 CFR 1.367(a)-6T - Transfer of foreign branch with previously deducted losses (temporary).

Code of Federal Regulations, 2014 CFR

2014-04-01

... recaptured by the recognition of the gain realized on the transfer. Paragraph (c) of this section sets forth rules concerning the character of, and limitations on, the gain required to be recognized. Paragraph (d... of gain required—(1) In general. If a U.S. person transfers any assets of a foreign branch to a...

26 CFR 1.367(a)-6T - Transfer of foreign branch with previously deducted losses (temporary).

Code of Federal Regulations, 2013 CFR

2013-04-01

... recaptured by the recognition of the gain realized on the transfer. Paragraph (c) of this section sets forth rules concerning the character of, and limitations on, the gain required to be recognized. Paragraph (d... of gain required—(1) In general. If a U.S. person transfers any assets of a foreign branch to a...

Alternating-Script Priming in Japanese: Are Katakana and Hiragana Characters Interchangeable?

ERIC Educational Resources Information Center

Perea, Manuel; Nakayama, Mariko; Lupker, Stephen J.

2017-01-01

Models of written word recognition in languages using the Roman alphabet assume that a word's visual form is quickly mapped onto abstract units. This proposal is consistent with the finding that masked priming effects are of similar magnitude from lowercase, uppercase, and alternating-case primes (e.g., beard-BEARD, BEARD-BEARD, and BeArD-BEARD).…

Intrinsic Motivation of Chinese Learning in Predicting Online Learning Self-Efficacy and Flow Experience Relevant to Students' Learning Progress

ERIC Educational Resources Information Center

Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Lin, Pei-Hsin

2017-01-01

Students of Southeast Asian Heritage Learning Chinese (SSAHLC) in Taiwan have frequently demonstrated difficulty with traditional Chinese (a graphical character) radical recognition due to their limited exposure to the written language form since childhood. In this study, we designed a Chinese radical learning game (CRLG), which adopted a drill…

Learning curve of speech recognition.

PubMed

Kauppinen, Tomi A; Kaipio, Johanna; Koivikko, Mika P

2013-12-01

Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new users become as skilled as the experienced users. We studied SR log entries for 0.25 million reports from 154 radiologists and after careful exclusions, defined a group of 11 experienced radiologists and 71 radiologists new to SR (24,833 and 122,093 reports, respectively). Data were analyzed for sound file and report lengths, character-based error rates, and words unknown to the SR's dictionary. Experienced radiologists corrected 6 characters for each report and for new users, 11. Some users presented a very unfavorable learning curve, with error rates not declining as expected. New users' reports were longer, and data for the experienced users indicates that their reports, initially equally lengthy, shortened over a period of several years. For most radiologists, only minor corrections of dictated reports were necessary. While new users adopted SR quickly, with a subset outperforming experienced users from the start, identification of users struggling with SR will help facilitate troubleshooting and support.

The joint effects of risk status, gender, early literacy and cognitive skills on the presence of dyslexia among a group of high-risk Chinese children.

PubMed

Wong, Simpson W L; McBride-Chang, Catherine; Lam, Catherine; Chan, Becky; Lam, Fanny W F; Doo, Sylvia

2012-02-01

This study sought to examine factors that are predictive of future developmental dyslexia among a group of 5-year-old Chinese children at risk for dyslexia, including 62 children with a sibling who had been previously diagnosed with dyslexia and 52 children who manifested clinical at-risk factors in aspects of language according to testing by paediatricians. The age-5 performances on various literacy and cognitive tasks, gender and group status (familial risk or language delayed) were used to predict developmental dyslexia 2 years later using logistic regression analysis. Results showed that greater risk of dyslexia was related to slower rapid automatized naming, lower scores on morphological awareness, Chinese character recognition and English letter naming, and gender (boys had more risk). Three logistic equations were generated for estimating individual risk of dyslexia. The strongest models were those that included all print-related variables (including speeded number naming, character recognition and letter identification) and gender, with about 70% accuracy or above. Early identification of those Chinese children at risk for dyslexia can facilitate better dyslexia risk management. Copyright © 2012 John Wiley & Sons, Ltd.

Slant correction for handwritten English documents

NASA Astrophysics Data System (ADS)

Shridhar, Malayappan; Kimura, Fumitaka; Ding, Yimei; Miller, John W. V.

2004-12-01

Optical character recognition of machine-printed documents is an effective means for extracting textural material. While the level of effectiveness for handwritten documents is much poorer, progress is being made in more constrained applications such as personal checks and postal addresses. In these applications a series of steps is performed for recognition beginning with removal of skew and slant. Slant is a characteristic unique to the writer and varies from writer to writer in which characters are tilted some amount from vertical. The second attribute is the skew that arises from the inability of the writer to write on a horizontal line. Several methods have been proposed and discussed for average slant estimation and correction in the earlier papers. However, analysis of many handwritten documents reveals that slant is a local property and slant varies even within a word. The use of an average slant for the entire word often results in overestimation or underestimation of the local slant. This paper describes three methods for local slant estimation, namely the simple iterative method, high-speed iterative method, and the 8-directional chain code method. The experimental results show that the proposed methods can estimate and correct local slant more effectively than the average slant correction.

Image remapping strategies applied as protheses for the visually impaired

NASA Technical Reports Server (NTRS)

Johnson, Curtis D.

1993-01-01

Maculopathy and retinitis pigmentosa (rp) are two vision defects which render the afflicted person with impaired ability to read and recognize visual patterns. For some time there has been interest and work on the use of image remapping techniques to provide a visual aid for individuals with these impairments. The basic concept is to remap an image according to some mathematical transformation such that the image is warped around a maculopathic defect (scotoma) or within the rp foveal region of retinal sensitivity. NASA/JSC has been pursuing this research using angle invariant transformations with testing of the resulting remapping using subjects and facilities of the University of Houston, College of Optometry. Testing is facilitated by use of a hardware device, the Programmable Remapper, to provide the remapping of video images. This report presents the results of studies of alternative remapping transformations with the objective of improving subject reading rates and pattern recognition. In particular a form of conformal transformation was developed which provides for a smooth warping of an image around a scotoma. In such a case it is shown that distortion of characters and lines of characters is minimized which should lead to enhanced character recognition. In addition studies were made of alternative transformations which, although not conformal, provide for similar low character distortion remapping. A second, non-conformal transformation was studied for remapping of images to aid rp impairments. In this case a transformation was investigated which allows remapping of a vision field into a circular area representing the foveal retina region. The size and spatial representation of the image are selectable. It is shown that parametric adjustments allow for a wide variation of how a visual field is presented to the sensitive retina. This study also presents some preliminary considerations of how a prosthetic device could be implemented in a practical sense, vis-a-vis, size, weight and portability.

Page segmentation using script identification vectors: A first look

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

Hochberg, J.; Cannon, M.; Kelly, P.

1997-07-01

Document images in which different scripts, such as Chinese and Roman, appear on a single page pose a problem for optical character recognition (OCR) systems. This paper explores the use of script identification vectors in the analysis of multilingual document images. A script identification vector is calculated for each connected component in a document. The vector expresses the closest distance between the component and templates developed for each of thirteen scripts, including Arabic, Chinese, Cyrillic, and Roman. The authors calculate the first three principal components within the resulting thirteen-dimensional space for each image. By mapping these components to red, green,more » and blue, they can visualize the information contained in the script identification vectors. The visualization of several multilingual images suggests that the script identification vectors can be used to segment images into script-specific regions as large as several paragraphs or as small as a few characters. The visualized vectors also reveal distinctions within scripts, such as font in Roman documents, and kanji vs. kana in Japanese. Results are best for documents containing highly dissimilar scripts such as Roman and Japanese. Documents containing similar scripts, such as Roman and Cyrillic will require further investigation.« less

Pen-chant: Acoustic emissions of handwriting and drawing

NASA Astrophysics Data System (ADS)

Seniuk, Andrew G.

The sounds generated by a writing instrument ('pen-chant') provide a rich and underutilized source of information for pattern recognition. We examine the feasibility of recognition of handwritten cursive text, exclusively through an analysis of acoustic emissions. We design and implement a family of recognizers using a template matching approach, with templates and similarity measures derived variously from: smoothed amplitude signal with fixed resolution, discrete sequence of magnitudes obtained from peaks in the smoothed amplitude signal, and ordered tree obtained from a scale space signal representation. Test results are presented for recognition of isolated lowercase cursive characters and for whole words. We also present qualitative results for recognizing gestures such as circling, scratch-out, check-marks, and hatching. Our first set of results, using samples provided by the author, yield recognition rates of over 70% (alphabet) and 90% (26 words), with a confidence of +/-8%, based solely on acoustic emissions. Our second set of results uses data gathered from nine writers. These results demonstrate that acoustic emissions are a rich source of information, usable---on their own or in conjunction with image-based features---to solve pattern recognition problems. In future work, this approach can be applied to writer identification, handwriting and gesture-based computer input technology, emotion recognition, and temporal analysis of sketches.

Visual attention: low-level and high-level viewpoints

NASA Astrophysics Data System (ADS)

Stentiford, Fred W. M.

2012-06-01

This paper provides a brief outline of the approaches to modeling human visual attention. Bottom-up and top-down mechanisms are described together with some of the problems that they face. It has been suggested in brain science that memory functions by trading measurement precision for associative power; sensory inputs from the environment are never identical on separate occasions, but the associations with memory compensate for the differences. A graphical representation for image similarity is described that relies on the size of maximally associative structures (cliques) that are found to reflect between pairs of images. This is applied to the recognition of movie posters, the location and recognition of characters, and the recognition of faces. The similarity mechanism is shown to model popout effects when constraints are placed on the physical separation of pixels that correspond to nodes in the maximal cliques. The effect extends to modeling human visual behaviour on the Poggendorff illusion.

Application of optical character recognition in thermal image processing

NASA Astrophysics Data System (ADS)

Chan, W. T.; Sim, K. S.; Tso, C. P.

2011-07-01

This paper presents the results of a study on the reliability of the thermal imager compared to other devices that are used in preventive maintenance. Several case studies are used to facilitate the comparisons. When any device is found to perform unsatisfactorily where there is a suspected fault, its short-fall is determined so that the other devices may compensate, if possible. This study discovered that the thermal imager is not suitable or efficient enough for systems that happen to have little contrast in temperature between its parts or small but important parts that have their heat signatures obscured by those from other parts. The thermal imager is also found to be useful for preliminary examinations of certain systems, after which other more economical devices are suitable substitutes for further examinations. The findings of this research will be useful to the design and planning of preventive maintenance routines for industrial benefits.

Face recognition by applying wavelet subband representation and kernel associative memory.

PubMed

Zhang, Bai-Ling; Zhang, Haihong; Ge, Shuzhi Sam

2004-01-01

In this paper, we propose an efficient face recognition scheme which has two features: 1) representation of face images by two-dimensional (2-D) wavelet subband coefficients and 2) recognition by a modular, personalised classification method based on kernel associative memory models. Compared to PCA projections and low resolution "thumb-nail" image representations, wavelet subband coefficients can efficiently capture substantial facial features while keeping computational complexity low. As there are usually very limited samples, we constructed an associative memory (AM) model for each person and proposed to improve the performance of AM models by kernel methods. Specifically, we first applied kernel transforms to each possible training pair of faces sample and then mapped the high-dimensional feature space back to input space. Our scheme using modular autoassociative memory for face recognition is inspired by the same motivation as using autoencoders for optical character recognition (OCR), for which the advantages has been proven. By associative memory, all the prototypical faces of one particular person are used to reconstruct themselves and the reconstruction error for a probe face image is used to decide if the probe face is from the corresponding person. We carried out extensive experiments on three standard face recognition datasets, the FERET data, the XM2VTS data, and the ORL data. Detailed comparisons with earlier published results are provided and our proposed scheme offers better recognition accuracy on all of the face datasets.

Watching More Closely: Shot Scale Affects Film Viewers’ Theory of Mind Tendency But Not Ability

PubMed Central

Rooney, Brendan; Bálint, Katalin E.

2018-01-01

Recent research debates the effects of exposure to narrative fiction on recognition of mental states in others and self, referred to as Theory of Mind. The current study explores the mechanisms by which such effects could occur in fictional film. Using manipulated film scenes, we conducted a between subject experiment (N = 136) exploring how film shot-scale affects viewers’ Theory of Mind. Specifically, in our methods we distinguish between the trait Theory of Mind abilities (ToM ability), and the state-like tendency to recognize mental states in others and self (ToM tendency). Results showed that close-up shots (compared to long shots) of a character was associated with higher levels of Theory of Mind tendency, when the facial expression was sad but not when it was neutral. And this effect did not transfer to other characters in the film. There was also no observable effect of character depiction on viewers’ general Theory of Mind ability. Together the findings suggest that formal and content features of shot scale can elicit Theory of Mind responses by directing attention toward character mental states rather than improving viewers’ general Theory of Mind ability. PMID:29387032

The orthographic sensitivity to written Chinese in the occipital-temporal cortex.

PubMed

Liu, Haicheng; Jiang, Yi; Zhang, Bo; Ma, Lifei; He, Sheng; Weng, Xuchu

2013-06-01

Previous studies have identified an area in the left lateral fusiform cortex that is highly responsive to written words and has been named the visual word form area (VWFA). However, there is disagreement on the specific functional role of this area in word recognition. Chinese characters, which are dramatically different from Roman alphabets in the visual form and in the form to phonological mapping, provide a unique opportunity to investigate the properties of the VWFA. Specifically, to clarify the orthographic sensitivity in the mid-fusiform cortex, we compared fMRI response amplitudes (Exp. 1) as well as the spatial patterns of response across multiple voxels (Exp. 2) between Chinese characters and stimuli derived from Chinese characters with different orthographic properties. The fMRI response amplitude results suggest the existence of orthographic sensitivity in the VWFA. The results from multi-voxel pattern analysis indicate that spatial distribution of the responses across voxels in the occipitotemporal cortex contained discriminative information between the different types of character-related stimuli. These results together suggest that the orthographic rules are likely represented in a distributed neural network with the VWFA containing the most specific information regarding a stimulus' orthographic regularity.

Watching More Closely: Shot Scale Affects Film Viewers' Theory of Mind Tendency But Not Ability.

PubMed

Rooney, Brendan; Bálint, Katalin E

2017-01-01

Recent research debates the effects of exposure to narrative fiction on recognition of mental states in others and self, referred to as Theory of Mind. The current study explores the mechanisms by which such effects could occur in fictional film. Using manipulated film scenes, we conducted a between subject experiment ( N = 136) exploring how film shot-scale affects viewers' Theory of Mind. Specifically, in our methods we distinguish between the trait Theory of Mind abilities (ToM ability), and the state-like tendency to recognize mental states in others and self (ToM tendency). Results showed that close-up shots (compared to long shots) of a character was associated with higher levels of Theory of Mind tendency, when the facial expression was sad but not when it was neutral. And this effect did not transfer to other characters in the film. There was also no observable effect of character depiction on viewers' general Theory of Mind ability. Together the findings suggest that formal and content features of shot scale can elicit Theory of Mind responses by directing attention toward character mental states rather than improving viewers' general Theory of Mind ability.

[Event-related potentials in character semantic priming of attention deficit hyperactivity disorder children and normal children: a comparative study].

PubMed

Xie, Na; Wang, Su-Hong; Ren, Yan-Ling; Ma, Ling; Dong, Xuan

2009-02-17

To investigate the cognitive event related potentials in Chinese character priming effect of children with attention deficit hyperactivity disorder (ADHD) and to analyze the neural mechanism of the priming effect. Fifty-two ADHD children aged (9.5 +/- 1.7) and 45 age-matched children without ADHD were asked to perform a Chinese character semantic priming task while electroencephalogram was recorded. During the Chinese character semantic priming task the subjects were instructed to judge whether the presented target word was a related word, unrelated word, or a pseudoword and event-related potentials (ERPs) were elicited and analyzed with the brain electricity source analysis (BESA) software. (1) The behavioral results showed that the reaction time to the unrelated character stimuli in the ADHD children was (1252 +/- 256) ms, significantly longer than that in the normal control [(1131 +/- 194) ms, P < 0.05]. (2) The amplitude of the character related N2 at the Cz lead in the ADHD children was -7.7 (-12.8, -5.0) microV, significantly larger than that of the normal controls [-5.6 (-9.4, -3.2) microV, P < 0.05]. (3) The amplitude of character unrelated stimuli P3 at the Cz lead of the ADHD children was 5.4 (2.0, 9.5) microV, significantly lower than that of the normal control [9.5 (4.2, 16.9) microV, P < 0.01]. There is a positive correlation between the amplitude of N2 and the difficulty in character semantic priming. It is more difficult for the ADHD children than normal controls to accomplish the same semantic task. ADHD children need more attention resources than normal controls. The amplitudes of character related-N2 and unrelated-P3 may become markers to measure the development of recognition in the ADHD children, thus being helpful in the ADHD diagnosis.

Experimental Realization of a Quantum Support Vector Machine

NASA Astrophysics Data System (ADS)

Li, Zhaokai; Liu, Xiaomei; Xu, Nanyang; Du, Jiangfeng

2015-04-01

The fundamental principle of artificial intelligence is the ability of machines to learn from previous experience and do future work accordingly. In the age of big data, classical learning machines often require huge computational resources in many practical cases. Quantum machine learning algorithms, on the other hand, could be exponentially faster than their classical counterparts by utilizing quantum parallelism. Here, we demonstrate a quantum machine learning algorithm to implement handwriting recognition on a four-qubit NMR test bench. The quantum machine learns standard character fonts and then recognizes handwritten characters from a set with two candidates. Because of the wide spread importance of artificial intelligence and its tremendous consumption of computational resources, quantum speedup would be extremely attractive against the challenges of big data.

Cuticular Compounds Bring New Insight in the Post-Glacial Recolonization of a Pyrenean Area: Deutonura deficiens Deharveng, 1979 Complex, a Case Study

PubMed Central

Porco, David; Bedos, Anne; Deharveng, Louis

2010-01-01

Background In most Arthropod groups, the study of systematics and evolution rely mostly on neutral characters, in this context cuticular compounds, as non-neutral characters, represent an underexplored but potentially informative type of characters at the infraspecific level as they have been routinely proven to be involved in sexual attraction. Methods and Findings The collembolan species complex Deutonura deficiens was chosen as a model in order to test the utility of these characters for delineating four infraspecific entities of this group. Specimens were collected for three subspecies (D. d. deficiens, D. d. meridionalis, D. d. sylvatica) and two morphotypes (D. d. sylvatica morphoype A and B) of the complex; an additional species D. monticola was added. Cuticular compounds were extracted and separated by gas chromatography for each individual. Our results demonstrate that cuticular compounds succeeded in separating the different elements of this complex. Those data allowed also the reconstruction of the phylogenetic relationships among them. Conclusions The discriminating power of cuticular compounds is directly related to their involvement in sexual attraction and mate recognition. These findings allowed a discussion on the potential involvement of intrinsic and paleoclimatic factors in the origin and the diversification of this complex in the Pyrenean zone. This character type brings the first advance from pattern to process concerning the origin of this species complex. PMID:21209797

Cuticular compounds bring new insight in the post-glacial recolonization of a Pyrenean area: Deutonura deficiens Deharveng, 1979 complex, a case study.

PubMed

Porco, David; Bedos, Anne; Deharveng, Louis

2010-12-21

In most Arthropod groups, the study of systematics and evolution rely mostly on neutral characters, in this context cuticular compounds, as non-neutral characters, represent an underexplored but potentially informative type of characters at the infraspecific level as they have been routinely proven to be involved in sexual attraction. The collembolan species complex Deutonura deficiens was chosen as a model in order to test the utility of these characters for delineating four infraspecific entities of this group. Specimens were collected for three subspecies (D. d. deficiens, D. d. meridionalis, D. d. sylvatica) and two morphotypes (D. d. sylvatica morphoype A and B) of the complex; an additional species D. monticola was added. Cuticular compounds were extracted and separated by gas chromatography for each individual. Our results demonstrate that cuticular compounds succeeded in separating the different elements of this complex. Those data allowed also the reconstruction of the phylogenetic relationships among them. The discriminating power of cuticular compounds is directly related to their involvement in sexual attraction and mate recognition. These findings allowed a discussion on the potential involvement of intrinsic and paleoclimatic factors in the origin and the diversification of this complex in the Pyrenean zone. This character type brings the first advance from pattern to process concerning the origin of this species complex.

Catholic Schools and Attitudes toward Religious Diversity: An Empirical Enquiry among 13- to 15-Year-Old Students in Scotland

ERIC Educational Resources Information Center

Francis, Leslie J.; Village, Andrew; Penny, Gemma; Neil, Peter

2014-01-01

Recognition that the United Kingdom has increasingly become a multi-cultural and multi-faith society has raised questions about the place of church schools or schools with a religious character within the state-maintained sector. The issue was given particular focus by the Runnymede Trusts report "Right to divide? Faith schools and community…

Association Rule Based Feature Extraction for Character Recognition

NASA Astrophysics Data System (ADS)

Dua, Sumeet; Singh, Harpreet

Association rules that represent isomorphisms among data have gained importance in exploratory data analysis because they can find inherent, implicit, and interesting relationships among data. They are also commonly used in data mining to extract the conditions among attribute values that occur together frequently in a dataset [1]. These rules have wide range of applications, namely in the financial and retail sectors of marketing, sales, and medicine.

Intelligent bar chart plagiarism detection in documents.

PubMed

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Rehman, Amjad; Alkawaz, Mohammed Hazim; Saba, Tanzila; Al-Rodhaan, Mznah; Al-Dhelaan, Abdullah

2014-01-01

This paper presents a novel features mining approach from documents that could not be mined via optical character recognition (OCR). By identifying the intimate relationship between the text and graphical components, the proposed technique pulls out the Start, End, and Exact values for each bar. Furthermore, the word 2-gram and Euclidean distance methods are used to accurately detect and determine plagiarism in bar charts.

Defense Against Threat. Threat Recognition and Analysis Project

DTIC Science & Technology

1975-09-01

but clustering around it ( land affecting it) are other action structures of different character, now entering strongly on the world scene...seeks .o cap ur ^^’^^try to gestalts of cognition and affect , ^[Jj^ f c!anrPr or country, that put the signature of...TRAMSPORT 8, PETROL PRODUCTS 7.*, USR 27, JAP 18, IND Ik, - FRUITS +NUTS Ik, NATURAL GAS 17, LAMBSKINS 12, USR 30, PAK

Intelligent Bar Chart Plagiarism Detection in Documents

PubMed Central

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Alkawaz, Mohammed Hazim; Saba, Tanzila; Al-Rodhaan, Mznah; Al-Dhelaan, Abdullah

2014-01-01

This paper presents a novel features mining approach from documents that could not be mined via optical character recognition (OCR). By identifying the intimate relationship between the text and graphical components, the proposed technique pulls out the Start, End, and Exact values for each bar. Furthermore, the word 2-gram and Euclidean distance methods are used to accurately detect and determine plagiarism in bar charts. PMID:25309952

Emotion Recognition in Frontotemporal Dementia and Alzheimer's Disease: A New Film-Based Assessment

PubMed Central

Goodkind, Madeleine S.; Sturm, Virginia E.; Ascher, Elizabeth A.; Shdo, Suzanne M.; Miller, Bruce L.; Rankin, Katherine P.; Levenson, Robert W.

2015-01-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. PMID:26010574

Figure Text Extraction in Biomedical Literature

PubMed Central

Kim, Daehyun; Yu, Hong

2011-01-01

Background Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. Methodology We first evaluated an off-the-shelf Optical Character Recognition (OCR) tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT) to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. Results/Conclusions The evaluation on 382 figures (9,643 figure texts in total) randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19.3% recall, and 25.3% F1-score for text extraction. In addition, our results show that FigTExT can extract texts that do not appear in figure captions or other associated text, further suggesting the potential utility of FigTExT for improving figure search. PMID:21249186

Figure text extraction in biomedical literature.

PubMed

Kim, Daehyun; Yu, Hong

2011-01-13

Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. We first evaluated an off-the-shelf Optical Character Recognition (OCR) tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT) to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. The evaluation on 382 figures (9,643 figure texts in total) randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19.3% recall, and 25.3% F1-score for text extraction. In addition, our results show that FigTExT can extract texts that do not appear in figure captions or other associated text, further suggesting the potential utility of FigTExT for improving figure search.

Functional and anatomical dissociation between the orthographic lexicon and the orthographic buffer revealed in reading and writing Chinese characters by fMRI.

PubMed

Chen, Hsiang-Yu; Chang, Erik C; Chen, Sinead H Y; Lin, Yi-Chen; Wu, Denise H

2016-04-01

The contribution of orthographic representations to reading and writing has been intensively investigated in the literature. However, the distinction between neuronal correlates of the orthographic lexicon and the orthographic (graphemic) buffer has rarely been examined in alphabetic languages and never been explored in non-alphabetic languages. To determine whether the neural networks associated with the orthographic lexicon and buffer of logographic materials are comparable to those reported in the literature, the present fMRI experiment manipulated frequency and the stroke number of Chinese characters in the tasks of form judgment and stroke judgment, which emphasized the processing of character recognition and writing, respectively. It was found that the left fusiform gyrus exhibited higher activation when encountering low-frequency than high-frequency characters in both tasks, which suggested this region to be the locus of the orthographic lexicon that represents the knowledge of character forms. On the other hand, the activations in the posterior part of the left middle frontal gyrus and in the left angular gyrus were parametrically modulated by the stroke number of target characters only in the stroke judgment task, which suggested these regions to be the locus of the orthographic buffer that represents the processing of stroke sequence in writing. These results provide the first evidence for the functional and anatomical dissociation between the orthographic lexicon and buffer in reading and writing Chinese characters. They also demonstrate the critical roles of the left fusiform area and the frontoparietal network to the long-term and short-term representations of orthographic knowledge, respectively, across different orthographies. Copyright © 2016 Elsevier Inc. All rights reserved.

Electronic patient registration and tracking at mass vaccination clinics: a clinical study.

PubMed

Billittier, Anthony J; Lupiani, Patrick; Masterson, Gary; Masterson, Tim; Zak, Christopher

2003-01-01

To protect the citizens of the United States from the use of dangerous biological agents, the Center for Disease Control and Prevention (CDC) has been actively preparing to deal with the consequences of such an attack. Their plans include the deployment of mass immunization clinics to handle postevent vaccinations. As part of the planning efforts by the Western New York Public Health Alliance, a Web-based electronic patient registration and tracking system was developed and tested at a recent trial smallpox vaccination clinic. Initial goals were to determine what the pitfalls and benefits of using such a system might be in comparison to other methods of data collection. This exercise proved that use of an electronic system capable of scanning two-dimensional bar codes was superior to both paper-based and optical character recognition (OCR) methods of data collection and management. Major improvements in speed and/or accuracy were evident in all areas of the clinic, especially in patient registration, vaccine tracking and postclinic data analysis.

Expert system for automatically correcting OCR output

NASA Astrophysics Data System (ADS)

Taghva, Kazem; Borsack, Julie; Condit, Allen

1994-03-01

This paper describes a new expert system for automatically correcting errors made by optical character recognition (OCR) devices. The system, which we call the post-processing system, is designed to improve the quality of text produced by an OCR device in preparation for subsequent retrieval from an information system. The system is composed of numerous parts: an information retrieval system, an English dictionary, a domain-specific dictionary, and a collection of algorithms and heuristics designed to correct as many OCR errors as possible. For the remaining errors that cannot be corrected, the system passes them on to a user-level editing program. This post-processing system can be viewed as part of a larger system that would streamline the steps of taking a document from its hard copy form to its usable electronic form, or it can be considered a stand alone system for OCR error correction. An earlier version of this system has been used to process approximately 10,000 pages of OCR generated text. Among the OCR errors discovered by this version, about 87% were corrected. We implement numerous new parts of the system, test this new version, and present the results.

The Effectiveness of Full Day School System for Students’ Character Building

NASA Astrophysics Data System (ADS)

Benawa, A.; Peter, R.; Makmun, S.

2018-01-01

The study aims to put forward that full day school which was delivered in Marsudirini Elementary School in Bogor is effective for students’ character building. The study focused on the implementation of full day school system. The qualitative-based research method applied in the study is characteristic evaluation involving non-participant observation, interview, and documentation analysis. The result of this study concludes that the full day school system is significantly effective in education system for elementary students’ character building. The full day school system embraced the entire relevant processes based on the character building standard. The synergy of comprehensive components in instructional process at full day school has influenced the building of the students’ character effectively and efficiently. The relationship emerged between instructional development process in full day school system and the character building of the students. By developing instructional process through systemic and systematic process in full day school system, the support of stakeholders (leaders, human resources, students, parents’ role) and other components (learning resources, facilities, budget) provides a potent and expeditious contribution for character building among the students eventually.

Teleform scannable data entry: an efficient method to update a community-based medical record? Community care coordination network Database Group.

PubMed Central

Guerette, P.; Robinson, B.; Moran, W. P.; Messick, C.; Wright, M.; Wofford, J.; Velez, R.

1995-01-01

Community-based multi-disciplinary care of chronically ill individuals frequently requires the efforts of several agencies and organizations. The Community Care Coordination Network (CCCN) is an effort to establish a community-based clinical database and electronic communication system to facilitate the exchange of pertinent patient data among primary care, community-based and hospital-based providers. In developing a primary care based electronic record, a method is needed to update records from the field or remote sites and agencies and yet maintain data quality. Scannable data entry with fixed fields, optical character recognition and verification was compared to traditional keyboard data entry to determine the relative efficiency of each method in updating the CCCN database. PMID:8563414

Reducing errors from the electronic transcription of data collected on paper forms: a research data case study.

PubMed

Wahi, Monika M; Parks, David V; Skeate, Robert C; Goldin, Steven B

2008-01-01

We conducted a reliability study comparing single data entry (SE) into a Microsoft Excel spreadsheet to entry using the existing forms (EF) feature of the Teleforms software system, in which optical character recognition is used to capture data off of paper forms designed in non-Teleforms software programs. We compared the transcription of data from multiple paper forms from over 100 research participants representing almost 20,000 data entry fields. Error rates for SE were significantly lower than those for EF, so we chose SE for data entry in our study. Data transcription strategies from paper to electronic format should be chosen based on evidence from formal evaluations, and their design should be contemplated during the paper forms development stage.

Reducing Errors from the Electronic Transcription of Data Collected on Paper Forms: A Research Data Case Study

PubMed Central

Wahi, Monika M.; Parks, David V.; Skeate, Robert C.; Goldin, Steven B.

2008-01-01

We conducted a reliability study comparing single data entry (SE) into a Microsoft Excel spreadsheet to entry using the existing forms (EF) feature of the Teleforms software system, in which optical character recognition is used to capture data off of paper forms designed in non-Teleforms software programs. We compared the transcription of data from multiple paper forms from over 100 research participants representing almost 20,000 data entry fields. Error rates for SE were significantly lower than those for EF, so we chose SE for data entry in our study. Data transcription strategies from paper to electronic format should be chosen based on evidence from formal evaluations, and their design should be contemplated during the paper forms development stage. PMID:18308994

Seed morphology and anatomy and its utility in recognizing subfamilies and tribes of Zingiberaceae

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

Benedict, John C.; Smith, Selena Y.; Collinson, Margaret E.

PREMISE OF THE STUDY: Recent phylogenetic analyses based on molecular data suggested that the monocot family Zingiberaceae be separated into four subfamilies and four tribes. Robust morphological characters to support these clades are lacking. Seeds were analyzed in a phylogenetic context to test independently the circumscription of clades and to better understand evolution of seed characters within Zingiberaceae. METHODS: Seventy-five species from three of the four subfamilies were analyzed using synchrotron based x-ray tomographic microscopy (SRXTM) and scored for 39 morphoanatomical characters. KEY RESULTS: Zingiberaceae seeds are some of the most structurally complex seeds in angiosperms. No single seed charactermore » was found to distinguish each subfamily, but combinations of characters were found to differentiate between the subfamilies. Recognition of the tribes based on seeds was possible for Globbeae, but not for Alpinieae, Riedelieae, or Zingibereae, due to considerable variation. CONCLUSIONS: SRXTM is an excellent, nondestructive tool to capture morphoanatomical variation of seeds and allows for the study of taxa with limited material available. Alpinioideae, Siphonochiloideae, Tamijioideae, and Zingiberoideae are well supported based on both molecular and morphological data, including multiple seed characters. Globbeae are well supported as a distinctive tribe within the Zingiberoideae, but no other tribe could be differentiated using seeds due to considerable homoplasy when compared with currently accepted relationships based on molecular data. Novel seed characters suggest tribal affinities for two currently unplaced Zingiberaceae taxa: Siliquamomum may be related to Riedelieae and Monolophus to Zingibereae, but further work is needed before formal revision of the family.« less

Correlating Petrophysical Well Logs Using Fractal-based Analysis to Identify Changes in the Signal Complexity Across Neutron, Density, Dipole Sonic, and Gamma Ray Tool Types

NASA Astrophysics Data System (ADS)

Matthews, L.; Gurrola, H.

2015-12-01

Typical petrophysical well log correlation is accomplished by manual pattern recognition leading to subjective correlations. The change in character in a well log is dependent upon the change in the response of the tool to lithology. The petrophysical interpreter looks for a change in one log type that would correspond to the way a different tool responds to the same lithology. To develop an objective way to pick changes in well log characteristics, we adapt a method of first arrival picking used in seismic data to analyze changes in the character of well logs. We chose to use the fractal method developed by Boschetti et al[1] (1996). This method worked better than we expected and we found similar changes in the fractal dimension across very different tool types (sonic vs density vs gamma ray). We reason the fractal response of the log is not dependent on the physics of the tool response but rather the change in the complexity of the log data. When a formation changes physical character in time or space the recorded magnitude in tool data changes complexity at the same time even if the original tool response is very different. The relative complexity of the data regardless of the tool used is dependent upon the complexity of the medium relative to tool measurement. The relative complexity of the recorded magnitude data changes as a tool transitions from one character type to another. The character we are measuring is the roughness or complexity of the petrophysical curve. Our method provides a way to directly compare different log types based on a quantitative change in signal complexity. For example, using changes in data complexity allow us to correlate gamma ray suites with sonic logs within a well and then across to an adjacent well with similar signatures. Our method creates reliable and automatic correlations to be made in data sets beyond the reasonable cognitive limits of geoscientists in both speed and consistent pattern recognition. [1] Fabio Boschetti, Mike D. Dentith, and Ron D. List, (1996). A fractal-based algorithm for detecting first arrivals on seismic traces. Geophysics, Vol.61, No.4, P. 1095-1102.

Development of an automated ultrasonic testing system

NASA Astrophysics Data System (ADS)

Shuxiang, Jiao; Wong, Brian Stephen

2005-04-01

Non-Destructive Testing is necessary in areas where defects in structures emerge over time due to wear and tear and structural integrity is necessary to maintain its usability. However, manual testing results in many limitations: high training cost, long training procedure, and worse, the inconsistent test results. A prime objective of this project is to develop an automatic Non-Destructive testing system for a shaft of the wheel axle of a railway carriage. Various methods, such as the neural network, pattern recognition methods and knowledge-based system are used for the artificial intelligence problem. In this paper, a statistical pattern recognition approach, Classification Tree is applied. Before feature selection, a thorough study on the ultrasonic signals produced was carried out. Based on the analysis of the ultrasonic signals, three signal processing methods were developed to enhance the ultrasonic signals: Cross-Correlation, Zero-Phase filter and Averaging. The target of this step is to reduce the noise and make the signal character more distinguishable. Four features: 1. The Auto Regressive Model Coefficients. 2. Standard Deviation. 3. Pearson Correlation 4. Dispersion Uniformity Degree are selected. And then a Classification Tree is created and applied to recognize the peak positions and amplitudes. Searching local maximum is carried out before feature computing. This procedure reduces much computation time in the real-time testing. Based on this algorithm, a software package called SOFRA was developed to recognize the peaks, calibrate automatically and test a simulated shaft automatically. The automatic calibration procedure and the automatic shaft testing procedure are developed.

The Influence of Chinese Character Handwriting Diagnosis and Remedial Instruction System on Learners of Chinese as a Foreign Language

ERIC Educational Resources Information Center

Hsiao, Hsien-Sheng; Chang, Cheng-Sian; Chen, Chiao-Jia; Wu, Chia-Hou; Lin, Chien-Yu

2015-01-01

This study designed and developed a Chinese character handwriting diagnosis and remedial instruction (CHDRI) system to improve Chinese as a foreign language (CFL) learners' ability to write Chinese characters. The CFL learners were given two tests based on the CHDRI system. One test focused on Chinese character handwriting to diagnose the CFL…

The National Eutrophication Survey: lake characteristics and historical nutrient concentrations

NASA Astrophysics Data System (ADS)

Stachelek, Joseph; Ford, Chanse; Kincaid, Dustin; King, Katelyn; Miller, Heather; Nagelkirk, Ryan

2018-01-01

Historical ecological surveys serve as a baseline and provide context for contemporary research, yet many of these records are not preserved in a way that ensures their long-term usability. The National Eutrophication Survey (NES) database is currently only available as scans of the original reports (PDF files) with no embedded character information. This limits its searchability, machine readability, and the ability of current and future scientists to systematically evaluate its contents. The NES data were collected by the US Environmental Protection Agency between 1972 and 1975 as part of an effort to investigate eutrophication in freshwater lakes and reservoirs. Although several studies have manually transcribed small portions of the database in support of specific studies, there have been no systematic attempts to transcribe and preserve the database in its entirety. Here we use a combination of automated optical character recognition and manual quality assurance procedures to make these data available for analysis. The performance of the optical character recognition protocol was found to be linked to variation in the quality (clarity) of the original documents. For each of the four archival scanned reports, our quality assurance protocol found an error rate between 5.9 and 17 %. The goal of our approach was to strike a balance between efficiency and data quality by combining entry of data by hand with digital transcription technologies. The finished database contains information on the physical characteristics, hydrology, and water quality of about 800 lakes in the contiguous US (Stachelek et al.(2017), https://doi.org/10.5063/F1639MVD). Ultimately, this database could be combined with more recent studies to generate meta-analyses of water quality trends and spatial variation across the continental US.

Adaptive detection of missed text areas in OCR outputs: application to the automatic assessment of OCR quality in mass digitization projects

NASA Astrophysics Data System (ADS)

Ben Salah, Ahmed; Ragot, Nicolas; Paquet, Thierry

2013-01-01

The French National Library (BnF*) has launched many mass digitization projects in order to give access to its collection. The indexation of digital documents on Gallica (digital library of the BnF) is done through their textual content obtained thanks to service providers that use Optical Character Recognition softwares (OCR). OCR softwares have become increasingly complex systems composed of several subsystems dedicated to the analysis and the recognition of the elements in a page. However, the reliability of these systems is always an issue at stake. Indeed, in some cases, we can find errors in OCR outputs that occur because of an accumulation of several errors at different levels in the OCR process. One of the frequent errors in OCR outputs is the missed text components. The presence of such errors may lead to severe defects in digital libraries. In this paper, we investigate the detection of missed text components to control the OCR results from the collections of the French National Library. Our verification approach uses local information inside the pages based on Radon transform descriptors and Local Binary Patterns descriptors (LBP) coupled with OCR results to control their consistency. The experimental results show that our method detects 84.15% of the missed textual components, by comparing the OCR ALTO files outputs (produced by the service providers) to the images of the document.

Figure mining for biomedical research.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan

2009-08-15

Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types. This study describes a retrieval method that takes advantage of principles in image understanding, text mining and optical character recognition (OCR) to retrieve figure types defined conceptually. A search engine was developed to retrieve tables and figure types to aid computational and experimental research. http://iossifovlab.cshl.edu/figurome/.

Automatic extraction of numeric strings in unconstrained handwritten document images

NASA Astrophysics Data System (ADS)

Haji, M. Mehdi; Bui, Tien D.; Suen, Ching Y.

2011-01-01

Numeric strings such as identification numbers carry vital pieces of information in documents. In this paper, we present a novel algorithm for automatic extraction of numeric strings in unconstrained handwritten document images. The algorithm has two main phases: pruning and verification. In the pruning phase, the algorithm first performs a new segment-merge procedure on each text line, and then using a new regularity measure, it prunes all sequences of characters that are unlikely to be numeric strings. The segment-merge procedure is composed of two modules: a new explicit character segmentation algorithm which is based on analysis of skeletal graphs and a merging algorithm which is based on graph partitioning. All the candidate sequences that pass the pruning phase are sent to a recognition-based verification phase for the final decision. The recognition is based on a coarse-to-fine approach using probabilistic RBF networks. We developed our algorithm for the processing of real-world documents where letters and digits may be connected or broken in a document. The effectiveness of the proposed approach is shown by extensive experiments done on a real-world database of 607 documents which contains handwritten, machine-printed and mixed documents with different types of layouts and levels of noise.

Study on photophysical and aggregation induced emission recognition of 1,8-naphthalimide probe for casein by spectroscopic method

NASA Astrophysics Data System (ADS)

Sun, Yang; Liu, Zhen; Liang, Xuhua; Fan, Jun; Han, Quan

2013-05-01

A novel water-soluble 1,8-naphthalimide derivative 1, bearing two acetic carboxylic groups, exhibited fluorescent turn-on recognition for casein based on the aggregation induced emission (AIE) character. The photophysical properties of 1 consisting of donor and acceptor units were investigated in different solutions. The fluorescence intensity decreased through taking advantage of twisted intramolecular charge transfer (TICT) and self-association emission with increasing solvent polarity. Moreover, the spectral red-shift and intensity quench in protic solvents were caused by the excited-state hydrogen bond strengthening effect. Density Functional Theory (DFT) calculations revealed that 1 exhibited a strong TICT character. The AIE mechanism of 1 with casein was due to 1 docked in the hydrophobic cavity between sub-micelles and bound with Tyr and Trp residues, resulting in the aggregation of 1 on the casein surface and emission enhancement. Based on this, a novel casein assay method was developed. The proposed exhibited a good linear range from 0.1 to 22 μg mL-1, with the detection limit of 2.8 ng mL-1. Satisfactory reproducibility, reversibility and a short response time were realized. This method was applied to the determination of casein in milk powder samples and the results were in good agreement with the result of Biuret method.

Insensitivity of visual short-term memory to irrelevant visual information.

PubMed

Andrade, Jackie; Kemps, Eva; Werniers, Yves; May, Jon; Szmalec, Arnaud

2002-07-01

Several authors have hypothesized that visuo-spatial working memory is functionally analogous to verbal working memory. Irrelevant background speech impairs verbal short-term memory. We investigated whether irrelevant visual information has an analogous effect on visual short-term memory, using a dynamic visual noise (DVN) technique known to disrupt visual imagery (Quinn & McConnell, 1996b). Experiment I replicated the effect of DVN on pegword imagery. Experiments 2 and 3 showed no effect of DVN on recall of static matrix patterns, despite a significant effect of a concurrent spatial tapping task. Experiment 4 showed no effect of DVN on encoding or maintenance of arrays of matrix patterns, despite testing memory by a recognition procedure to encourage visual rather than spatial processing. Serial position curves showed a one-item recency effect typical of visual short-term memory. Experiment 5 showed no effect of DVN on short-term recognition of Chinese characters, despite effects of visual similarity and a concurrent colour memory task that confirmed visual processing of the characters. We conclude that irrelevant visual noise does not impair visual short-term memory. Visual working memory may not be functionally analogous to verbal working memory, and different cognitive processes may underlie visual short-term memory and visual imagery.

Characterizing Mobility and Contact Networks in Virtual Worlds

NASA Astrophysics Data System (ADS)

Machado, Felipe; Santos, Matheus; Almeida, Virgílio; Guedes, Dorgival

Virtual worlds have recently gained wide recognition as an important field of study in Computer Science. In this work we present an analysis of the mobility and interactions among characters in World of Warcraft (WoW) and Second Life based on the contact opportunities extracted from actual user data in each of those domains. We analyze character contacts in terms of their spatial and temporal characteristics, as well as the social network derived from such contacts. Our results show that the contacts observed may be more influenced by the nature of the interactions and goals of the users in each situation than by the intrinsic structure of such worlds. In particular, observations from a city in WoW are closer to those of Second Life than to other areas in WoW itself.

Taxonomic etymology – in search of inspiration

PubMed Central

Jóźwiak, Piotr; Rewicz, Tomasz; Pabis, Krzysztof

2015-01-01

Abstract We present a review of the etymology of zoological taxonomic names with emphasis on the most unusual examples. The names were divided into several categories, starting from the most common – given after morphological features – through inspiration from mythology, legends, and classic literature but also from fictional and nonfictional pop-culture characters (e.g., music, movies or cartoons), science, and politics. A separate category includes zoological names created using word-play and figures of speech such as tautonyms, acronyms, anagrams, and palindromes. Our intention was to give an overview of possibilities of how and where taxonomists can find the inspirations that will be consistent with the ICZN rules and generate more detail afterthought about the naming process itself, the meaningful character of naming, as well as the recognition and understanding of names. PMID:26257573

Differential theory of learning for efficient neural network pattern recognition

NASA Astrophysics Data System (ADS)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-09-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.