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A new dataset of Persian handwritten documents and its segmentation

A new dataset of Persian handwritten documents and its segme...

引用

2011 7th Iranian Conference on Machine vision and Image Processing, MVIP 2011

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)9781457715358

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. © 2011 IEEE.

关键词： Image segmentation

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A new two-stage scheme for the recognition of persian handwritten characters

A new two-stage scheme for the recognition of persian handwr...

引用

International Conference on Frontiers in Handwriting recognition

ISBN: (纸本)9780769542218

In this paper, a two-stage scheme for the recognition of Persian handwritten isolated characters is proposed. In the first stage, similar shaped characters are categorized into groups and as a result, 8 groups are obtained from 32 Persian basic characters. In the second stage, the groups containing more than one similar shape characters are considered further for the final recognition. Feature extraction is based on undersampled bitmaps technique and modified chain-code direction frequencies. For the first stage features, we compute 49-dimension features based on undersampled bitmaps from 49 non-overlapping 7x7 window-maps. 196-dimension chain-code direction frequencies from 49 overlapping 9x9 window-maps are computed and used as features for the second stage of the proposed scheme. Classifiers are one-against-other support vector machines (SVM). We evaluated our scheme on a standard dataset of Persian handwritten characters. Using 36682 samples for training, we tested our scheme on other 15338 samples and obtained 98.10% and 96.68% correct recognition rates when considered 8-class and 32-class problems, respectively. © 2010 IEEE.

关键词： Support vector machines

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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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RDMMLND: A New Robust Deep Model for Multiple License Plate Number Detection in Video 3rd

RDMMLND: A New Robust Deep Model for Multiple License Plate ...

引用

3rd International Conference on pattern recognition and Artificial Intelligence, ICPRAI 2022

作者： Kumar, Amish Shivakumara, Palaiahnakote Pal, Umapada Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9783031090363

Accurate multiple license plate detection without affecting speed, occlusion, low contrast and resolution, uneven illumination effect and poor quality is an open challenge. This study presents a new Robust Deep Model for Multiple License Plate Number Detection (RDMMLND). To cope with the above-mentioned challenges, the proposed work explores YOLOv5 for detecting vehicles irrespective of type to reduce background complexity in the images. For detected vehicle regions, we propose a new combination of Wavelet Decomposition and Phase Congruency Model (WD-PCM), which enhances the license plate number region such that the license plate number detection step fixes correct bounding boxes for each vehicle of the input images. The proposed model is tested on our own dataset containing video images and standard dataset of license plate number detection to show that the proposed model is useful and effective for multiple license plate number detection. Furthermore, the proposed method is tested on natural scene text datasets to show that the proposed method can be extended to address the challenges of natural scene text detection. © 2022, Springer Nature Switzerland AG.

关键词： Wavelet decomposition

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A baseline dependent approach for Persian handwritten character segmentation

A baseline dependent approach for Persian handwritten charac...

引用

International Conference on pattern recognition

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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Document-zone classification in torn documents

Document-zone classification in torn documents

引用

International Conference on Frontiers in Handwriting recognition

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

ISBN: (纸本)9780769542218

Arbitrary orientation and sparse data content are common characteristics of torn document. To ensure accuracy and reliability in computer-based analysis, content-zone segmentation is required. In our previous work, we studied segmentation of handwritten and printed text. A questioned document-piece in the form of an office note, however, might also contain non-text data like logos, graphics, and pictures. Hence a more precise content-zone classification is required. In this paper we propose a two-Tier approach for non-text, handwriting and printed text segmentation. The first Tier aims to discriminate text and non-text regions. The second Tier classifies handwritten and printed text within all text zones identified during the first Tier. Gabor features and chain-code features are used in Tier-1 and Tier-2, respectively. By using SVM classifier we successfully identified 97.65% of 31,227 text regions in our current test data. The proposed approach identified 98.69% of printed and 96.39% of handwritten text amongst all identified text regions. © 2010 IEEE.

关键词： Text processing

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Off-line signature verification systems: A survey 11

Off-line signature verification systems: A survey

引用

Proceedings of the International Conference & Workshop on Emerging Trends in Technology

作者： Pal, S. Blumenstein, M. Pal, U. School of Information and Communication Technology Griffith University QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9781450304498

Signatures are extensively used as a means of personal verification. Manual signature-based authentication of a large number of documents is a very difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable physical unique characteristics (hand geometry, iris scan, finger prints or DNA) or behavioural features. Human signatures provide secure means for confirmation and authorization in legal documents. So nowadays, automatic signature verification becomes an essential component. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of off-line signature verification systems. Copyright © 2011 ACM.

关键词： Biometrics

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Non-english and non-latin signature verification systems: A survey

Non-english and non-latin signature verification systems: A ...

引用

1st International Workshop on Automated Forensic Handwriting Analysis, AFHA 2011 - A Satellite Workshop of ICDAR 2011

作者： Pal, Srikanta Blumenstein, Michael Pal, Umapada School of Information and Communication Technology Griffith University QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

Signatures continue to be an important biometric because they remain widely used as a means of personal verification and therefore an automatic verification system is needed. Manual signature-based authentication of a large number of documents is a difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable unique physical characteristics (e.g. hand geometry, iris scan, finger prints or DNA) or behavioural features. Substantial research has been undertaken in the field of signature verification involving English signatures, but to the best of our knowledge, very few works have considered non-English signatures such as Chinese, Japanese, Arabic etc. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of non-English and non-Latin signature verification systems.

关键词： Biometrics

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A rough set based approach for ECG classification

引用

作者： Mitra, Sucharita Mitra, M. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Department of Applied Physics Faculty of Technology University of Calcutta Kolkata India

ISBN: (纸本)3540898751

An inference engine for classification of Electrocardiogram (ECG) signals is developed with the help of a rule based rough set decision system. For this purpose an automated data extraction system from ECG strips is being developed by using a few image processing techniques. A knowledge base is developed after consulting different medical books as well as feedback of reputed cardiologists on interpretation and selection of essential time-plane features of ECG signal. An algorithm for extraction of different time domain features is also developed with the help of differentiation techniques and syntactic approaches. Finally, a rule-based rough set decision system is generated using these time-plane features for the development of an inference engine for disease classification. Two sets of rules are generated for this purpose. The first set is for general separation between normal and diseased subjects. The second set of rules is used for classifications between different diseases. © 2008 Springer Berlin Heidelberg.

关键词： Electrocardiograms

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Bangla date field extraction in offline handwritten documents 12

Bangla date field extraction in offline handwritten document...

引用

Workshop on Document Analysis and recognition, DAR 2012

作者： Mandal, Ranju Roy, Partha Pratim Pal, Umapada Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Laboratoire d'Informatique Université François Rabelais Tours France

ISBN: (纸本)9781450317979

Date is a useful information for various application (e.g. date wise document indexing) and automatic extraction of date information involves difficult challenges due to writing styles of different individuals, touching characters and confusion among identification of numerals, punctuation and texts. In this paper, we present a framework for indexing/retrieval of Bangla date patterns from handwritten documents. The method first classifies word components of each text line into month and non-month class using word level feature. Next, non-month words are segmented into individual components and classified into one of text, digit or punctuation. Using this information of word and character level components, the date patterns are searched. First using voting approach and then using regular expression we detect the candidate lines for numeric and semi-numeric date. Dynamic Time Warping (DTW) matching of profile based features is used for classification of month/non-month words. Numerals and punctuations are classified using gradient based feature and SVM classifier. The experiment is performed on Bangla handwritten dataset and the results demonstrate the effectiveness of the proposed system. © 2012 ACM.

关键词： Extraction

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