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Word-wise handwritten Persian and Roman script identification

Word-wise handwritten Persian and Roman script identificatio...

引用

International Conference on Frontiers in Handwriting recognition

作者： Roy, Kaushik Alaei, Alireza Pal, Umapada Department of Computer Science West Bengal State University Kolkata-126 India Department of Studies in Computer Science University of Mysore Mysore 570 006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9780769542218

Most of the countries use bi-script documents. This is because every country uses its own national language and English as second/foreign language. Therefore, bi-lingual document with one language being the English and other being the national language is very common. Postal documents are a very good example of such bi-lingual/script document. This paper deals with word-wise handwritten script identification from bi-script documents written in Persian and Roman. In the proposed scheme, simple but fast computable set of 12 features based on fractal dimension, position of small component, topology etc. are used and a set of classifiers are employed for script identification experiments. We tested our scheme on a dataset of 5000 handwritten Persian and English words and 99.20% of correct script identification is obtained. © 2010 IEEE.

关键词： Fractal dimension

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Shape Code Based Word-Image Matching for Retrieval of indian Multi-lingual Documents

Shape Code Based Word-Image Matching for Retrieval of Indian...

引用

International Conference on pattern recognition

作者： Arundhati Tarafdar Ranju Mondal Srikanta Pal Umapada Pal Fumitaka Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Japan

ISBN: (纸本)9781424475421

In the current scenario retrieving information from document images is a challenging problem. In this paper we propose a shape code based word-image matching (word-spotting) technique for retrieval of multilingual documents written in indian languages. Here, each query word image to be searched is represented by a primitive shape code using (i) zonal information of extreme points (ii) vertical shape based feature (iii) crossing count (with respect to vertical bar position) (iv) loop shape and position (v) background information etc. Each candidate word (a word having similar aspect ratio and topological feature to the query word) of the document is also coded accordingly. Then, an inexact string matching technique is used to measure the similarity between the primitive codes generated from the query word image and each candidate word of the document with which the query image is to be searched. Based on the similarity score, we retrieve the document where the query image is found. Experimental results on Bangla, Devnagari and Gurumukhi scripts document image databases confirm the feasibility and efficiency of our proposed approach.

关键词： Shape Encoding Image coding Image segmentation Feature extraction pattern recognition computer vision

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A New Symmetry Based on Proximity of Wavelet-Moments for Text Frame Classification in Video

A New Symmetry Based on Proximity of Wavelet-Moments for Tex...

引用

International Conference on pattern recognition

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

This paper proposes the use of a new symmetry property based on proximity of the median moments in the wavelet domain. The method divides a given frame into 16 equally sized blocks to classify the true text frame. The average of high frequency subbands of a block is used for computing median moments to brighten the text pixel in a block of video frame. Then K-means clustering with K=2 is applied on the median moments of the block to classify it as a probable text block. For classified blocks, average wavelet median moments are computed for a sliding window. We introduce Max-Min cluster to classify the probable text pixel in each probable text block. The four quadrants are formed from the centroid of the probable text pixels. The new concept called symmetry is introduced to identify the true text block based on proximity between probable text pixels in each quadrant. If the frame produces at least one true text block, it is considered as a text frame otherwise a non-text frame. The method is tested on three datasets to evaluate the robustness of the method in classification of text frames in terms of recall and precision.

关键词： Pixel Chromium Feature extraction pattern recognition Robustness Silicon Classification algorithms

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Document-Zone Classification in Torn Documents

Document-Zone Classification in Torn Documents

引用

International Workshop on Frontiers in Handwriting recognition

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

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.

关键词： Accuracy Graphics Gabor filters Support vector machines Pixel Feature extraction 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...

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International Workshop on Frontiers in Handwriting recognition

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 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 under sampled bitmaps technique and modified chain-code direction frequencies. For the first stage features, we compute 49-dimension features based on under sampled bitmaps from 49 non-overlapping 7 × 7 window-maps. 196-dimension chain-code direction frequencies from 49 overlapping 9 × 9 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.

关键词： Character recognition Feature extraction Shape Support vector machines Accuracy Handwriting recognition Pixel

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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)9781424475421

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 we obtained 93.49% correct segmentation accuracy.

关键词： Image segmentation Handwriting recognition Shape Algorithm design and analysis Equations Smoothing methods Feature extraction

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Bangla and english city name recognition for indian postal automation

Bangla and english city name recognition for Indian postal a...

引用

International Conference on pattern recognition

作者： Pal, Umapada Roy, Ramit Kumar Kimura, Fumitaka Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India St. Xavier's College 30 Park Street Kolkata-16 India Graduate School of Engg. Mie University 1577 Kurimamachiya-cho Tsu 514-8507 Japan

ISBN: (纸本)9780769541099

Because of multi-lingual behavior destination address block of a postal document of an indian state may be written in two or more scripts. From a statistical analysis of indian postal document we noted that about 22.04% of indian postal documents are written in two scripts. Because of inter-mixing of these scripts in postal address writings, it is very difficult to identify the script by which a city name is written. To avoid such identification difficulties, in this paper we proposed a lexicon-driven bi-lingual (English and Bangla) city name recognition scheme for indian postal automation. We obtained 93.19% accuracy when tested on 11875 city name samples. © 2010 IEEE.

关键词： Automation

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Color Feature Based Approach for Determining Ink Age in Printed Documents

Color Feature Based Approach for Determining Ink Age in Prin...

引用

International Conference on pattern recognition

作者： Biswajit Halder Utpal Garain Department of Information Technology Mallabhum Institute of Technology Bisnupur West Bengal India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

Answering to a query like when a particular document was printed is quite helpful in practice especially forensic purposes. This study attempts to develop a general framework that makes use of image processing and pattern recognition principles for ink age determination in printed documents. The approach, at first, computationally extracts a set of suitable color features and then analyzes them to properly associate them with ink age. Finally, a neural net is designed and trained to determine ages of unknown samples. The dataset used for the present experiment consists of the cover pages of LIFE magazines published in between 1930's and 70's (five decades). Test results show that a viable framework for involving machines in assisting human experts for determining age of printed documents.

关键词： Ink Image color analysis Feature extraction Pixel Forensics Artificial neural networks Accuracy

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A New Method for Handwritten Scene Text Detection in Video

A New Method for Handwritten Scene Text Detection in Video

引用

International Workshop on Frontiers in Handwriting recognition

作者： Palaiahnakote Shivakumara Anjan Dutta Umapada Pal Chew Lim Tan School of Computing National University of Singapore Singapore Computer Vision Center Universitat Authnòma de Barcelona Barcelona Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

There are many video images where hand written text may appear. Therefore handwritten scene text detection in video is essential and useful for many applications for efficient indexing, retrieval etc. Also there are many video frames where text line may be multi-oriented in nature. To the best of our knowledge there is no work on handwritten text detection in video, which is multi-oriented in nature. In this paper, we present a new method based on maximum color difference and boundary growing method for detection of multi-oriented handwritten scene text in video. The method computes maximum color difference for the average of R, G and B channels of the original frame to enhance the text information. The output of maximum color difference is fed to a K-means algorithm with K = 2 to separate text and non-text clusters. Text candidates are obtained by intersecting the text cluster with the Sobel output of the original frame. To tackle the fundamental problem of different orientations and skews of handwritten text, boundary growing method based on a nearest neighbor concept is employed. We evaluate the proposed method by testing on our own handwritten text database and publicly available video data (Hua's data). Experimental results obtained from the proposed method are promising.

关键词： Pixel Image edge detection Image color analysis Graphics Clustering algorithms Image resolution Measurement

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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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