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A complete automatic short answer assessment system with student identification

A complete automatic short answer assessment system with stu...

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International Conference on Document Analysis and recognition

作者： Hemmaphan Suwanwiwat Michael Blumenstein Umapada Pal School of Information and Communication Technology Griffith University Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

There are only a few studies undertaken in developing automatic assessment systems using handwriting recognition, even though a successful system would undoubtedly benefit the education system as schools and universities in many countries still employ paper-based examinations. To the best of the authors' knowledge, there is no existing work on an automatic off-line short answer assessment system comprising a student identification component. Hence in this paper, the authors propose a system towards this, where a new feature extraction technique called the Enhanced Water Reservoir, Loop and Gaussian Grid Feature, as well as other enhanced feature extraction techniques were utilised. Artificial Neural Networks and Support Vector Machines were employed as the classifiers; they were used for the investigation, and a comparison of the recognition and accuracy rates of the proposed systems, as well as the feature extraction techniques, was undertaken. The proposed assessment system achieved a recognition rate of 87.12% with 91.12% assessment accuracy, and the student identification component obtained a recognition rate of 99.52% with a 100% identification accuracy rate.

关键词： Feature extraction Field effect transistors Erbium

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Short Answer Question Examination using an Automatic Off-line Handwriting recognition System and a Novel Combined Feature

Short Answer Question Examination using an Automatic Off-lin...

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International Joint Conference on Neural Networks

ISBN: (纸本)9781479919611

Off-line automatic assessment systems can be an aid for teachers in the marking process. There has been no recent work in the development of off-line automatic assessment systems using handwriting recognition, even though such systems will clearly benefit the education sector. The reason is many schools and universities in many parts of the world still use paper-based examination. This research proposes the use of a newly developed feature extraction technique called the Modified Water Reservoir, Loop and Gaussian Grid Feature, as well as other feature extraction techniques. These techniques were investigated employing artificial neural networks and support vector machines as classifiers to develop an automatic assessment system for marking short answer questions. The system has high assessment accuracy (up to 94.75% for hand printed, 96.09% for cursive handwritten, and 95.71% for hand printed and cursive handwritten combined). The proposed system also includes assessment criteria to augment its accuracy.

关键词： Handwriting recognition Off-line Automatic Assessment System Modified direction feature Gaussian grid feature Water Reservoir Feature Modified Water Reservoir Loop and Gaussian Grid Feature handwriting recognition AUTOMATIC Feature extraction OFF LINE Hand Answer Classifiers Support Vector Network

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An efficient line segmentation approach for handwritten Bangla document image

An efficient line segmentation approach for handwritten Bang...

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International Conference on Advances in pattern recognition (ICAPR)

作者： K. Mullick S. Banerjee U. Bhattacharya Department of Computer Science and Engineering Heritage Institute of Technology Kolkata India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

Text line segmentation plays a vital role in the overall performance of a document recognition system. In the literature, similar segmentation works for offline handwritten Bangla documents are rarely found. On the other hand, certain peculiarities of handwritten Bangla script such as widespread occurrences of ascenders and descenders or some of its characters appearing only as an ascender or descender often cause unique difficulties to this segmentation task. Existence of connected components over a number of successive text lines is a common phenomenon in unconstrained handwritten Bangla documents. In this article, we propose a novel and efficient approach for text line segmentation where initially, we smudge the input document image, to blur-out white spaces between words, while preserving gaps between consecutive lines. Next, we obtain an initial segmentation scheme by shredding the image based on the white most pixels in between consecutive smudged lines. Multi-line connected components have been taken care of by thinning, and then finding the most probable point of separation in the component. Combining it with the initial segmentation, we obtain the final output. The proposed approach has been evaluated on ICDAR 2013 Handwriting Segmentation Contest dataset of Bangla. The segmentation results show the efficiency of the proposed approach.

关键词： Image segmentation Junctions Image color analysis Estimation Transforms Handwriting recognition Frequency modulation

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ICDAR2015 Competition on Video Script Identification (CVSI 2015)

ICDAR2015 Competition on Video Script Identification (CVSI 2...

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International Conference on Document Analysis and recognition

作者： Nabin Sharma Ranju Mandal Rabi Sharma Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Queensland Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479918065

This paper presents the final results of the ICDAR 2015 Competition on Video Script Identification. A description and performance of the participating systems in the competition are reported. The general objective of the competition is to evaluate and benchmark the available methods on word-wise video script identification. It also provides a platform for researchers around the globe to particularly address the video script identification problem and video text recognition in general. The competition was organised around four different tasks involving various combinations of scripts comprising tri-script and multiscript scenarios. The dataset used in the competition comprised ten different scripts. In total, six systems were received from five participants over the tasks offered. This report details the competition dataset specifications, evaluation criteria, summary of the participating systems and their performance across different tasks. The systems submitted by Google Inc. were the winner of the competition for all the tasks, whereas the systems received from Huazhong University of Science and Technology (HUST) and computer vision Center (CVC) were very close competitors.

关键词： Video scripts identification multi-lingual OCR multi-lingual video-text competition

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Performance evaluation of DTW and its variants for word spotting in degraded documents

Performance evaluation of DTW and its variants for word spot...

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International Conference on Document Analysis and recognition

作者： Tanmoy Mondal Nicolas Ragot Jean-Yves Ramel Umapada Pal Université François Rabelais Laboratory of Computer Science (LI) Tours France Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479918065

In word spotting literature, classical DTW has been widely employed. However there exists several other improved versions of DTW along with other robust sequence matching techniques. Very few of them have been studied in the context of word spotting and this scarcity of research work is the motivation of the paper. This paper presents a comparative study of classical Dynamic Time Warping (DTW) technique and many of its improved modifications, as well as other sequence matching techniques in the context of word spotting. An experimental study on historical documents is performed to evaluate the behavior of DTW's variants and other sequence matching techniques. A detailed comparative analysis along with wide range of experimentation is performed, which shows that classical DTW remains a good choice when there are no segmentation problems and when features are very local. In case of word segmentation errors, Continuous Dynamic Programming (CDP) seems to be a better choice. This research work has introduced several other improved sequence matching algorithms in the context of word spotting, which show interesting and improved results.

关键词： Biomedical imaging Biomedical measurement

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Exemplary Sequence Cardinality: An Effective Application for Word Spotting

Exemplary Sequence Cardinality: An Effective Application for...

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International Conference on Document Analysis and recognition

作者： Tanmoy Mondal Nicolas Ragot Jean-Yves Ramel Umapada Pal Université Fran?ois Rabelais Tours Laboratory of Computer Science (LI) Tours France. Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India.

ISBN: (纸本)9781479918065

In this paper, a new sequence matching algorithm called as Exemplary Sequence Cardinality (ESC) is proposed. ESC combines several abilities of other sequence matching algorithms e.g. DTW, SSDTW, CDP, FSM, MVM, OSB~1. Depending on the application domain, ESC can be tuned to behave such as these different sequence matching algorithms. Its generality and robustness comes from its ability to find subsequences (as in CDP and SSDTW), to skip outliers inside the target sequences (as in MVM and FSM) and also in the query sequence (as in OSB) and it has the ability to have many to one and one to many correspondences (as in DTW) between the elements of the query and the target sequences. It's special characteristic of skipping noisy elements from query sequence along with other afore mentioned properties gives it an edge over FSM. In case of word spotting application, the outliers skipping capability of ESC makes it less sensible to local variations in the spelling of words, and also to noise present in the query and/or in the target word images. Due to it's capability of sub-sequence matching, the ESC algorithm has the ability to retrieve a query inside a line or piece of line. Finally, its multiple matching facilities (many to one and one to many matching) is proven to be well advantageous in case of different length of target and query sequences due to the variability in scale, font, type/size factors. By experimenting on printed historical document images, we have demonstrated the interest of proposed ESC algorithm in specific cases when incorrect word segmentation and word level local variations occur regularly.

关键词： Word spotting Elastic sequence matching Minimal variance matching (MVM) Optimal sequence bijection (OSB) Dynamic time warping (DTW) Continuous dynamic programming (CDP) Flexible sequence matching (FSM)

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An approach for character segmentation of handwritten Bangla and devanagari script

An approach for character segmentation of handwritten Bangla...

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IEEE International Advance Computing Conference, IACC

作者： Anmol J Bhattad Bidyut B. Chaudhuri Electronics & Communication Engineering National Institute of Technology Karnataka Surathkal Mangalore India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479980482

In this paper a scheme for segmentation of unconstrained handwritten Devanagari and Bangla words into characters and its sub-parts is proposed. Firstly, the region above headline is identified by counting the number of white to black transitions in each row, which followed by its separation. Then the characters are segmented using fuzzy logic. For each column, the inputs to the fuzzy system are the location of first white pixel, thickness of the first black stroke, count of white pixels, and the run length count of white pixels.

关键词： Indexes Robustness

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Automated scoring of Bender Gestalt Test using image analysis techniques

Automated scoring of Bender Gestalt Test using image analysi...

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International Conference on Document Analysis and recognition

作者： Momina Moetesum Imran Siddiqi Uzma Masroor Chawki Djeddi Center of Computer Vision and Pattern Recognition Bahria University Islamabad Pakistan Dept. of Professional Psychology Bahria University Islamabad Pakistan LAMIS Laboratory Larbi Tebessi University Tebessa Algeria

ISBN: (纸本)9781479918065

Drawing tests have been long used by practitioners and researchers for early detection of psychological and neurological impairments. These tests allow subjects to naturally express themselves as opposed to an interview or a written assessment. Bender Gestalt Test (BGT) is a well-known and established neurological test designed to detect signs of perceptual distortions. Subjects are shown a number of geometric patterns for reconstruction and assessments are made by observing properties like rotation, angulations, simplification and closure difficulty. The manual scoring of the test, however, is a time consuming and lengthy procedure especially when a large number of subjects is to be analyzed. This paper proposes the application of image analysis techniques to automatically score a subset of hand drawn images in the BGT test. A comparison of the scores reported by the automated system with those assigned by the psychologists not only reveals the effectiveness of the proposed system but also reflects the huge research potential this area possesses.

关键词： Manuals Psychology Biomedical imaging Computational modeling

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New texture-spatial features for keyword spotting in video images

New texture-spatial features for keyword spotting in video i...

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Asian Conference on pattern recognition (ACPR)

作者： Palaiahnakote Shivakumara Guozhu Liang Sangheeta Roy Umapada Pal Tong Lu Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia National Key Lab for Novel Software Technology Nanjing University Nanjing China Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479961016

Keyword spotting in video document images is challenging due to low resolution and complex background of video images. We propose the combination of Texture-Spatial-Features (TSF) for keyword spotting in video images without recognizing them. First, a segmentation method extracts words from text lines in each video image. Then we propose the set of texture features for identifying text candidates in the word image with the help of k-means clustering. The proposed method finds proximity between text candidates to study the spatial arrangement of pixels that result in feature vectors for spotting words in the input frame. The proposed method is evaluated on word images of different fonts, contrasts, backgrounds and font sizes, which are chosen from standard databases such as ICDAR 2013 video and our video data. Experimental results show that the proposed method outperforms the existing method in terms of recall, precision and f-measure.

关键词： Image segmentation Semantics Video signal processing Indexing pattern recognition Spatial resolution

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3D reconstruction based on light field information

3D reconstruction based on light field information

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International Conference on Information and Automation (ICIA)

作者： Yan Zhou Huiwen Guo Ruiqing Fu Guoyuan Liang Can Wang Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong

ISBN: (纸本)9781467391054

As an important branch of computational photography, light field photography combines the hardware design of optical system with key algorithm of signal processing quite well. Unlike traditional photography which can only record light ray's two-dimensional position, light field photography system can record four-dimensional position and direction. Therefore, much more image information can be obtained from light field photography. With the development of 3D display technology, light field based autofocus and 3D display technology is becoming more and more popular. In this paper, a light field based new 3D reconstruction algorithm for buildings and office environment is proposed by applying Wavelet Transform and SVM (Support Vector Machine) model to obtain the image focusing quality assessment, along with the Mean Shift Algorithm and Random Field Model to get the depth map of the scene. Firstly, light field image is captured by using a light field camera. Secondly, we use frequency domain digital refocus algorithm to manipulate light field image and obtain several serialized refocused images with different focus. Thirdly, wavelet features are extracted from each refocused image, and then an image focusing quality assessment is conducted by using RBF (Radial Basis Function) kernel based SVM model. Finally, we use Mean Shift algorithm to realize color clustering of the original light field image, and then build MRF (Markov Random Field) Model with color nodes. By iterating the likelihood depth result obtained from real scenario depth calibrations according to image focusing quality assessment, finally the depth map of the scene is reconstructed. Experiments are conducted to prove the feasibility of the proposed 3D reconstructed algorithm based on light field. And the experimental results on real datasets demonstrate good performance of this algorithm.

关键词： Three-dimensional displays Cameras Photography Lenses Wavelet transforms Focusing

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