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Segmentation of Bangla handwritten text into characters by recursive contour following 5

Segmentation of Bangla handwritten text into characters by r...

引用

5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Bishnu, A. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta700035 India

ISBN: (纸本)0769503187

Segmentation of handwritten words into characters is one of the important components in handwritten text OCR. In this paper we put forward a method for the segmentation of handwritten Bangla (an Indo-Bangladeshi language) text into characters. Based on certain characteristics of Bangla writing methods, different zones across the height of the word are detected. These zones provide certain structural information about the constituent characters of the respective word. In Bangla handwritten texts often there is overlap between rectangular hulls of successive characters. As such the characters are seldom vertically separable. So, we propose a method of recursive contour following in one of the zones across the height of the word to find out the extents within which the main portion of the character lies. If the successive characters are not touching in the zone of contour following, the algorithm gives fairly good results. © 1999 IEEE.

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CNN based common approach to handwritten character recognition of multiple scripts 13

CNN based common approach to handwritten character recogniti...

引用

13th International Conference on Document Analysis and recognition, ICDAR 2015

作者： Maitra, Durjoy Sen Bhattacharya, Ujjwal Parui, Swapan K. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata-108 India

ISBN: (纸本)9781479918058

There are many scripts in the world, several of which are used by hundreds of millions of people. Handwritten character recognition studies of several of these scripts are found in the literature. Different hand-crafted feature sets have been used in these recognition studies. However, convolutional neural network (CNN) has recently been used as an efficient unsupervised feature vector extractor. Although such a network can be used as a unified framework for both feature extraction and classification, it is more efficient as a feature extractor than as a classifier. In the present study, we performed certain amount of training of a 5-layer CNN for a moderately large class character recognition problem. We used this CNN trained for a larger class recognition problem towards feature extraction of samples of several smaller class recognition problems. In each case, a distinct Support Vector Machine (SVM) was used as the corresponding classifier. In particular, the CNN of the present study is trained using samples of a standard 50-class Bangla basic character database and features have been extracted for 5 different 10-class numeral recognition problems of English, Devanagari, Bangla, Telugu and Oriya each of which is an official Indian script. recognition accuracies are comparable with the state-of-the-art. © 2015 IEEE.

关键词： Character recognition

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A novel technique for the watermarking of symbolically compressed documents

A novel technique for the watermarking of symbolically compr...

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International Workshop on Document Image Analysis for Libraries

作者： S. Palit U. Garain Computer Vision and Pattern Recognition Unit

Symbolic compression is a lossy compression technique which has been found to perform very efficiently for Indian language text document images. A novel and efficient watermarking technique is proposed for such documents compressed symbolically. The approach embeds the watermark into prototypes which are unaffected during compression, leading to an exact recovery of the watermark both from the compressed document and the reconstructed one. The watermark is perfectly resistant to JPEG conversion and reasonably resistant to other attacks. The proposed technique, for the first time, combines the compression and watermarking of Indian language text document images in a common framework

关键词： Watermarking Image coding Data encapsulation Image storage Image reconstruction Prototypes Immune system Software libraries Communication standards computer vision

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Script line separation from Indian multi-script documents 5

Script line separation from Indian multi-script documents

引用

5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Pal, U. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta35 India

ISBN: (纸本)0769503187

In a multi-lingual country like India, a document page may contain more than one script form. Under the three-language formula, the document may be printed in English, Devnagari and one of the other official Indian languages. For OCR of such a document page, it is necessary to separate these three script forms before feeding them to the OCRs of individual scripts. In this paper, an automatic technique of separating the text lines using script characteristics and shape based features is presented. At present, the system has an overall accuracy of about 98.5%. © 1999 IEEE.

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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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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 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 ...

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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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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 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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Machine authentication of security documents

Machine authentication of security documents

引用

ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Garain, Utpal Halder, Biswajit Computer Vision and Pattern Recognition Unit India Statistical Institute 203 B.T. Road Kolkata 700108 India WB India

ISBN: (纸本)9780769537252

This paper presents a pioneering effort towards machine authentication of security documents like bank cheques, legal deeds, certificates, etc. that fall under the same class as far as security is concerned. The proposed method first computationally extracts the security features from the document images and then the notion of 'genuine' vs. 'duplicate' is defined in the feature space. Bank cheques are taken as a reference for conducting the present experiment. Support Vector Machines (SVMs) and Neural Networks (NN) are involved to verify authenticity of these cheques. Results on a test dataset of 200 samples show that the proposed approach achieves about 98% accuracy for discriminating duplicate cheques from genuine ones. This strongly attests the viability of involving machine in authenticating security documents. © 2009 IEEE.

关键词： Support vector machines

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