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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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A New Method for Word Segmentation from Arbitrarily-Oriented Video Text Lines

A New Method for Word Segmentation from Arbitrarily-Oriented...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Nabin Sharma Palaiahnakote Shivakumara Umapada Pal Michael Blumenstein Chew Lim Tan Griffith University Queensland Australia School of Computing National University of Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Word segmentation has become a research topic to improve OCR accuracy for video text recognition, because a video text line suffers from arbitrary orientation, complex background and low resolution. Therefore, for word segmentation from arbitrarily-oriented video text lines, in this paper, we extract four new gradient directional features for each Canny edge pixel of the input text line image to produce four respective pixel candidate images. The union of four pixel candidate images is performed to obtain a text candidate image. The sequence of the components in the text candidate image according to the text line is determined using nearest neighbor criteria. Then we propose a two-stage method for segmenting words. In the first stage, for the distances between the components, we apply K-means clustering with K=2 to get probable word and non-word spacing clusters. The words are segmented based on probable word spacing and all other components are passed to the second stage for segmenting correct words. For each segmented and un-segmented words passed to the second stage, the method repeats all the steps until the K-means clustering step to find probable word and non-word spacing clusters. Then the method considers cluster nature, height and width of the components to identify the correct word spacing. The method is tested extensively on video curved text lines, non-horizontal straight lines, horizontal straight lines and text lines from the ICDAR-2003 competition data. Experimental results and a comparative study shows the results are encouraging and promising.

关键词： Image segmentation Image edge detection Feature extraction Text recognition Optical character recognition software Vectors Image resolution

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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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Detection of QRS complex of ECG signals from square-derivative curve

Modelling, Measurement and Control C

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Modelling, Measurement and Control C 2004年第1-2期65卷 15-27页

作者： Mitra, S. Mitra, M. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata 700108 India Department of Applied Physics University College of Science and Tech. University of Calcutta Kolkata 700009 India

An approach to QRS complex detection based on the selection of maximum area zone of square derivative curve is presented in this paper. At first the ECG signals are being extracted from paper ECG records by an automated data acquisition system which has been developed by using image processing techniques. Then the QRS complex of each ECG signal is detected even in the presence of power line interference and baseline drift to calculate the sampling period for further analysis in frequency plane for disease identification. A very high accuracy level (∼ 99.4%) has been achieved in detection of QRS complex by this method.

关键词： computer vision

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A Fast Word Retrieval Technique Based on Kernelized Locality Sensitive Hashing

A Fast Word Retrieval Technique Based on Kernelized Locality...

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International Conference on Document Analysis and recognition

作者： Tanmoy Mondal Nicolas Ragot Jean-Yves Ramel Umapada Pal Laboratoire dInformatique Université François Rabelais de Tours Tours France Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479901937

In this paper, we have presented a new and faster word retrieval approach, which is able to deal with heterogeneous document image collections. A certain amount of image features (statistical and Gabor Wavelet) are extracted, which inherently represent word's images. These features are used for generating hash table for fast retrieval of similar image from a very large image dataset. The decomposition and embedding of high-dimensional features and complex distance functions into a low-dimensional Hamming space helps to efficiently search items. However, existing methods do not apply for high-dimensional kernelized data when the underlying features' embedding for the kernel is unknown. The generalization of locality sensitive hashing (LSH) for arbitrary kernel is presented in the paper. The proposed algorithm provides sub-linear time similarity search and works for a wide class of similarity functions.

关键词： Feature extraction Kernel Databases Accuracy Vectors Training pattern recognition

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An Automatic Off-Line Short Answer Assessment System Using Novel Hybrid Features

An Automatic Off-Line Short Answer Assessment System Using N...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Hemmaphan Suwanwiwat Umapada Pal Michael Blumenstein College of Business James Cook University Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute India School of Software University of Technology Sydney Australia

To date, paper-based examinations are still in use worldwide on all levels of education levels (e.g. secondary, tertiary levels). However, literature regarding off-line automatic assessment systems employing off-line handwriting recognition is not numerous. This paper proposes an off-line automatic assessment system employing a hybrid feature extraction technique - a newly proposed Modified Direction and Gaussian Grid Feature (MDGGF), along with its enhanced technique. In this study other original feature extraction techniques, together with their enhanced features, were also used for feature extraction technique efficiency comparison purposes. Classifiers, namely artificial neural networks and support vector machines, were selected to be employed in the experiments. Two types of datasets were employed in the experiment for both feature extraction technique accuracy and efficiency comparisons. The best correctly recognised rate of 98.33% with 100% accuracy was obtained when employing the proposed MDGGF to the off-line automatic assessment system.

关键词： Feature extraction Gravity Training Testing Artificial neural networks Support vector machines Handwriting recognition

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A Painting Based Technique for Skew Estimation of Scanned Documents

A Painting Based Technique for Skew Estimation of Scanned Do...

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International Conference on Document Analysis and recognition

作者： Alireza Alaei Umapada Pal P. Nagabhushan Fumitaka Kimura Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Japan

In this paper, we propose an efficient skew estimation technique based on Piece-wise Painting Algorithm (PPA) for scanned documents. Here we, at first, employ the PPA on the document image horizontally and vertically. Applying the PPA on both the directions, two painted images (one for horizontally painted and other for vertically painted) are obtained. Next, based on statistical analysis some regions with specific height (width) from horizontally (vertically) painted images are selected and top (left), middle (middle) and bottom (right) points of such selected regions are categorized in 6 separate lists. Utilizing linear regression, a few lines are drawn using the lists of points. A new majority voting approach is also proposed to find the best-fit line amongst all the lines. The skew angle of the document image is estimated from the slope of the best-fit line. The proposed technique was tested extensively on a dataset containing various categories of documents. Experimental results showed that the proposed technique achieved more accurate results than the state-of-the-art methodologies.

关键词： Estimation Painting Fitting Linear regression Text analysis Writing

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Text Independent Writer Identification for Bengali Script

Text Independent Writer Identification for Bengali Script

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International Conference on pattern recognition

作者： Sukalpa Chanda Katrin Franke Umapada Pal Tetsushi Wakabayashi Department of Computer Science and Media Technology Gjovik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Graduate School of Engineering Mie University Japan

ISBN: (纸本)9781424475421

Automatic identification of an individual based on his/her handwriting characteristics is an important forensic tool. In a computational forensic scenario, presence of huge amount of text/information in a questioned document cannot be always ensured. Also, compromising in terms of systems reliability under such situation is not desirable. We here propose a system to encounter such adverse situation in the context of Bengali script. Experiments with discrete directional feature and gradient feature are reported here, along with Support Vector Machine (SVM) as classifier. We got promising results of 95.19% writer identification accuracy at first top choice and 99.03% when considering first three top choices.

关键词： Accuracy Support vector machines Training Handwriting recognition Forensics Text analysis

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Neural Information Processing 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Nikhil Ranjan Pal Nik Kasabov Rajani K. Mudi Srimanta Pal Swapan Kumar Parui

ISBN: (数字)9783540304999

ISBN: (纸本)9783540239314

It is our great pleasure to welcome you to the 11th International Conference on Neural Information Processing (ICONIP 2004) to be held in Calcutta. ICONIP 2004 is organized jointly by the Indian Statistical Institute (ISI) and Jadavpur University (JU). We are con?dent that ICONIP 2004, like the previous conf- ences in this series,will providea forum for fruitful interactionandthe exchange of ideas between the participants coming from all parts of the globe. ICONIP 2004 covers all major facets of computational intelligence, but, of course, with a primary emphasis on neural networks. We are sure that this meeting will be enjoyable academically and otherwise. We are thankful to the track chairs and the reviewers for extending their support in various forms to make a sound technical program. Except for a few cases, where we could get only two review reports, each submitted paper was reviewed by at least three referees, and in some cases the revised versions were againcheckedbythereferees. Wehad470submissionsanditwasnotaneasytask for us to select papers for a four-day conference. Because of the limited duration of the conference, based on the review reports we selected only about 40% of the contributed papers. Consequently, it is possible that some good papers are left out. We again express our sincere thanks to all referees for accomplishing a great job. In addition to 186 contributed papers, the proceedings includes two plenary presentations, four invited talks and 18 papers in four special sessions. The proceedings is organized into 26 coherent topical groups.

关键词： Artificial Intelligence Computation by Abstract Devices pattern recognition Image Processing and computer vision Probability and Statistics in computer Science Algorithm Analysis and Problem Complexity

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Script Identification – A Han and Roman Script Perspective

Script Identification – A Han and Roman Script Perspective

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International Conference on pattern recognition

作者： Sukalpa Chanda Umapada Pal Katrin Franke Fumitaka Kimura Department of Computer Science and Media Technology Gjovik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Graduate School of Engineering Mie University Japan

All Han-based scripts (Chinese, Japanese, and Korean) possess similar visual characteristics. Hence system development for identification of Chinese, Japanese and Korean scripts from a single document page is quite challenging. It is noted that a Han-based document page might also have Roman script in them. A multi-script OCR system dealing with Chinese, Japanese, Korean, and Roman scripts, demands identification of scripts before execution of respective OCR modules. We propose a system to address this problem using directional features along with a Gaussian Kernel-based Support Vector Machine. We got promising results of 98.39% script identification accuracy at character level and 99.85% at block level, when no rejection was considered.

关键词： Accuracy Support vector machines Training Kernel Feature extraction Image segmentation Optical character recognition software

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