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A New Dataset of Persian Handwritten Documents and Its Segmentation

A New Dataset of Persian Handwritten Documents and Its Segme...

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Iranian Machine vision and Image Processing (MVIP)

作者： Alireza Alaei P. Nagabhushan Umapada Pal Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In document image analysis and especially in handwritten document image recognition, standard datasets play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. In this paper, an unconstrained Persian handwritten text dataset (PHTD) is introduced. The PHTD contains 140 handwritten documents of three different categories written by 40 individuals. Total number of text-lines and words/subwords in the dataset are 1787 and 27073, respectively. In most of the PHTD documents either an overlapping or a touching text-lines is present. The average number of text-lines in documents of the PHTD is 13. Two types of ground truths based on pixels information and content information are generated for the dataset. Providing these two types of ground truths for the PHTD, it can be utilized in many areas of document image processing such as sentence recognition/understanding, text-line segmentation, word segmentation, word recognition, and character segmentation. To provide a framework for other researches, recent text-line segmentation results on this dataset are also reported.

关键词： Image segmentation Handwriting recognition Databases Character recognition Image recognition Text recognition

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A New Text-Line Alignment Approach Based on Piece-Wise Painting Algorithm for Handwritten Documents

A New Text-Line Alignment Approach Based on Piece-Wise Paint...

引用

International Conference on Document Analysis and recognition

Because of writing styles of different individuals, some of the text-lines may be curved in shape. For recognition of such text-lines, their proper alignment is necessary. In this paper, we propose a text-line alignment technique based on painting algorithm. Here at first, Piece-wise Painting Algorithm (PPA) is used to get a number of black and white rectangular patches all along the text-line for text-line alignment. Identifying the degree of oscillation of the input text-line, some candidate pixels are also obtained based on horizontal projection and center points of the black patches. Using the degree of oscillation of the input text image and the candidate pixels a curve or straight line is fit to trace the baseline. Subsequently, all components of the text-line are deskewed based on analyzing the characteristic of the fit curve or line to align the components with respect to the horizontal imaginary baseline. The proposed algorithm was evaluated with 128 Persian handwritten text-lines containing 4317 sub words. Experimental analysis showed that 92.31% of the sub words were accurately aligned. Further, the proposed algorithm was tested with another Persian handwritten text-lines dataset [6] and remarkable results were achieved.

关键词： Oscillators Painting Polynomials Algorithm design and analysis Curve fitting Estimation pattern recognition

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A Benchmark Kannada Handwritten Document Dataset and Its Segmentation

A Benchmark Kannada Handwritten Document Dataset and Its Seg...

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International Conference on Document Analysis and recognition

Research towards Indian handwritten document analysis achieved increasing attention in recent years. In pattern recognition and especially in handwritten document recognition, standard databases play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. For Indian languages, there is a lack of standard database of handwritten texts to evaluate performance of different document recognition approaches and for comparison purpose. In this paper, an unconstrained Kannada handwritten text database (KHTD) is introduced. The KHTD contains 204 handwritten documents of four different categories written by 51 native speakers of Kannada. Total number of text-lines and words in the dataset are 4298 and 26115, respectively. In most of text-pages of the KHTD contains either an overlapping or a touching text-lines and the average number of text-lines in each document on the database is 21. Two types of ground truths based on pixels information and content information are generated for the database. Providing these two types of ground truths for the KHTD, it can be utilized in many areas of document image processing such as sentence recognition/understanding, text-line segmentation, word segmentation, word recognition, and character segmentation. To provide a framework for other researches, recent text-line segmentation results on this dataset are also reported. The KHTD is available for research purposes.

关键词： Databases Image segmentation Handwriting recognition Character recognition Training Testing

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A novel approach for delineation and feature extraction in QRS complex of ECG signal

A novel approach for delineation and feature extraction in Q...

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2011 International Conference on Image Information Processing, ICIIP 2011

作者： Pramanik, Sayak Mitra, Rupendra Nath Mitra, Sucharita Chaudhuri, Bidyut Baran Department of Electronics and Communication Institute of Engineering and Management Kolkata India Network Planning and Optimization Nokia Siemens Networks Pvt. Ltd. Kolkata India Department of Electronics Netaji Nagar Day College Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781612848617

This paper reports the development of a software suite to be accessed in future with any General Packet Radio Service (GPRS) enabled mobile phone or Personal Digital Assistant (PDA) for the extraction and analysis of disease-related features from the images of paper based ECG records. In India and other developing countries, the cheaper paper based ECG machines are mainly used. Also in rural areas of these countries - where there is acute dearth of qualified cardiologists, the cardiac diseases are still the major silent killers. One way of addressing this problem is cellular medicine which necessitates an intelligent cardiac parameter extraction algorithm. In our bid to address exactly this requirement, a software is developed with the help of few image processing techniques. At first, the background noises i.e. the gridlines are removed by thresholding technique. Binarization and thinning has been done for extraction of digital time data and then Discrete Wavelet Transform (DWT) and water reservoir based pattern recognition technique are subsequently used to delineate other important ECG parameters for ECG interpretation. © 2011 IEEE.

关键词： Electrocardiograms

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Identification of Indic Scripts on Torn-Documents

Identification of Indic Scripts on Torn-Documents

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International Conference on Document Analysis and recognition

作者： Sukalpa Chanda Katrin Franke Umapada Pal Department of Computer Science and Media Technology Gjøvik University College Gjovik Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Questioned Document Examination processes often encompass analysis of torn documents. To aid a forensic expert, automatic classification of content type in torn documents might be useful. This helps a forensic expert to sort out similar document fragments from a pile of torn documents. One parameter of similarity could be the script of the text. In this article we propose a method to identify the script in document fragments. Torn documents are normally characterized by text with arbitrary orientation. We use Zernike moment - based feature that is rotation invariant together with Support Vector Machine (SVM) to classify the script type. Subsequently gradient features are used for comparative analysis of results between rotation dependent and rotation invariant feature type. We achieved an overall script-identification accuracy of 81.39% when dealing with 11 different scripts at character/connected-component level and 94.65% at word level.

关键词： Feature extraction Accuracy Support vector machines Kernel Training Labeling Forensics

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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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Off-line Signature Identification Using Background and Foreground Information

Off-line Signature Identification Using Background and Foreg...

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

作者： Srikanta Pal Alaei Alireza Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Gold Coast Australia Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Biometric systems play an important role in the field of information security as they are extremely required for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is currently receiving renewed interest and is only one of several techniques used to verify the identities of individuals. Signatures provide a secure means for confirmation and authorization in legal documents. So nowadays, signature identification and verification becomes an essential component in automating the rapid processing of documents containing embedded signatures. In this paper, a technique for a bi-script off-line signature identification system is proposed. In the proposed signature identification system, the signatures of English and Bengali (Bangla) are considered for the identification process. Different features such as under sampled bitmaps, modified chain-code direction features and gradient features computed from both background and foreground components are employed for this purpose. Support Vector Machines (SVMs) and Nearest Neighbour (NN) techniques are considered as classifiers for signature identification in the proposed system. A database of 1554 English signatures and 1092 Bengali signatures are used to generate the experimental results. Various results based on different features are calculated and analysed. The highest accuracies of 99.41%, 98.45% and 97.75% are obtained based on the modified chain-code direction, under-sampled bitmaps and gradient features respectively using 1800 (1100 English+700 Bengali) samples for training and 846 (454 English+392 Bengali) samples for testing.

关键词： Feature extraction Support vector machines Handwriting recognition Training Educational institutions Kernel Databases

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A novel approach for delineation and feature extraction in QRS complex of ECG signal

A novel approach for delineation and feature extraction in Q...

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International Conference on Image Information Processing

作者： Sayak Pramanik Rupendra Nath Mitra Sucharita Mitra Bidyut Baran Chaudhuri Department of Electronics & Communication Institute of Engineering and Management Kolkata India Department of Electronics Netaji Nagar Day College Kolkata India Network Planning & Optimization Nokia Siemens Networks Private Limited Kolkata India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

关键词： Electrocardiography Feature extraction pattern recognition Information processing Reservoirs Strips

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A new wavelet-median-moment based method for multi-oriented video text detection 10

A new wavelet-median-moment based method for multi-oriented ...

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2010 IAPR Workshop on Document Analysis Systems, DAS 2010

作者： Shivakumara, Palaiahnakote Dutta, Anjan Tan, Chew Lim Pal, Umapada Department of Computer Science School of Computing National University of Singapore Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781605587738

In this paper, we present a new method based on wavelet-median-moments and a novel idea of angle projection for detecting multi-oriented text in video. The proposed method uses wavelet decomposition first to obtain three high frequency sub-bands (LH, HL and HH) and then median moments are computed on the average sub-bands of the three high frequency sub-bands to brighten the text pixels. K-means clustering (K=2) is used for obtaining text pixels from the wavelet-median-moments features (WMMF). Text candidates are obtained by mapping the output of K-means on Sobel edge map of the original input frame. To deal with multi-oriented text, we introduce a new idea of Angle Projection (AP) based on boundary growing and nearest neighbor concepts from the text candidates instead of conventional projection profiles. The proposed method is experimented on horizontal text data, non-horizontal text data, temporal data, non-text data and camera based images (scene text data of ICDAR 2003 competition) to show that the proposed method is superior to existing methods. © Copyright 2010 ACM.

关键词： Pixels

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A baseline dependent approach for Persian handwritten character segmentation

A baseline dependent approach for Persian handwritten charac...

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International Conference on pattern recognition

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9780769541099

In this paper, an efficient approach to segment Persian off-line handwritten text-line into characters is presented. The proposed algorithm first traces the baseline of the input text-line image and straightens it. Subsequently, it over-segments each word/subwords using features extracted from histogram analysis and then removes extra segmentation points using some baseline dependent as well as language dependent rules. We tested the proposed character segmentation scheme with 2 different datasets. On a test set of 899 Persian words/subwords created by us, 90.26% of the characters were segmented correctly. From another dataset of 200 handwritten Arabic word images [11] we obtained 93.49% correct segmentation accuracy. © 2010 IEEE.

关键词： Image segmentation

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