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arXiv 2023年

作者： Roy, Prasun Ghosh, Subhankar Pal, Umapada Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Air-writing refers to virtually writing linguistic characters through hand gestures in three-dimensional space with six degrees of freedom. This paper proposes a generic video camera-aided convolutional neural network (CNN) based air-writing framework. Gestures are performed using a marker of fixed color in front of a generic video camera, followed by color-based segmentation to identify the marker and track the trajectory of the marker tip. A pre-trained CNN is then used to classify the gesture. The recognition accuracy is further improved using transfer learning with the newly acquired data. The performance of the system varies significantly on the illumination condition due to color-based segmentation. In a less fluctuating illumination condition, the system is able to recognize isolated unistroke numerals of multiple languages. The proposed framework has achieved 97.7%, 95.4% and 93.7% recognition rates in person independent evaluations on English, Bengali and Devanagari numerals, respectively. © 2023, CC BY.

关键词： Convolutional neural networks

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Multi-skew detection of Indian script documents

Multi-skew detection of Indian script documents

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International Conference on Document Analysis and recognition

作者： U. Pal M. Mitra B.B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India

ISBN: (纸本)0769512631

There are many documents where text lines are not parallel to each other i.e. these lines have different inclinations with the horizontal lines (multi-skew documents). For the OCR of such a document we have to estimate the skew angle of individual text lines because a single rotation cannot de-skew all text lines of the document. In this paper, we describe a robust technique for multi-skew angle detection from Indian documents containing the most popular Indian scripts Devnagari and Bangla. Most characters in these scripts have horizontal lines at the top, called head-lines. The character head-lines usually connect one another in a word and the word appears as a single component. In the proposed method, the connected components are at first labeled and selected. The upper envelopes of selected components are found by column-wise scanning from the top of the component. Portions of the upper envelope satisfying the properties of a digital straight line are detected. They are then clustered into groups belonging to single text lines. Estimates from these individual clusters give the skew angle of each text line. The proposed multi-skew detection technique has an accuracy about 98.3%.

关键词： Strips Fourier transforms Optical character recognition software Robustness computer vision pattern recognition Envelope detectors Humans Goniometers Gray-scale

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A system for word-wise handwritten script identification for Indian postal automation

A system for word-wise handwritten script identification for...

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IEEE India Conference (INDICON)

作者： K. Roy A. Banerjee U. Pal Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Postal automation is a topic of research over the last few years. There are many works towards the postal automation in USA, UK, Japan and Australia, but for Indian postal automation there is no significant work. This paper deals with word-wise handwritten script identification for Indian postal automation. In the proposed scheme at first document skew is detected and corrected. Non-text parts are then segmented from the document using run length smoothing algorithm (RLSA). Next, using a piece-wise projection method the destination address block (DAB) is at first segmented into lines and then links into words. Using water reservoir concept we compute the busy-zone of the word. Finally, using matra/Shirorekha, water reservoir concept based feature, etc. a tree classifier is generated for word-wise Bangla/Devnagari and English scripts identification.

关键词： Automation Natural languages Water resources Reservoirs Optical character recognition software Australia Smoothing methods Seals Histograms Feature extraction

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Robust stereo on multiple resolutions

Robust stereo on multiple resolutions

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13th International Conference on pattern recognition, ICPR 1996

作者： Menard, Christian Leonardis, Aleš Department for Pattern Recognition and Image Processing Technical University Vienna Treitlstraße 3/1832 3A-1040 Vienna Austria University of Ljubljana Faculty of Computer and Information Science Computer Vision Laboratory Ljubljana Slovenia

ISBN: (纸本)081867282X

Stereo computation is one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results that cannot be corrected in subsequent postprocessing stages. In this paper we present a modification of the standard area-based correlation approach so that it can tolerate a significant number of outliers. The approach exhibits a robust behavior not only in the presence of mismatches but also in the case of depth discontinuities. The confidence measure of the correlation and the number of outliers provide two complementary sources of information which, when implemented in a multiresolution framework, result in a robust and efficient method. We present the results of this approach on a number of synthetic and real images. © 1996 IEEE.

关键词： Stereo image processing

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Online handwritten Indian script recognition: a human motor function based framework

Online handwritten Indian script recognition: a human motor ...

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International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri T.T. Pal Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)076951695X

This paper presents the online handwriting recognition for Indian scripts. The primary concern of the approach is the modeling of human motor functionality while writing characters. This is achieved by looking at the whole pen trajectory where the time evaluation of the pen coordinates plays a crucial role. A low complexity classifier was designed and the proposed similarity measure appears to be quite robust against wide variations in writing styles. Initially, the approach was applied for online recognition of handwritten characters in Devnagari and Bangla, the two major Indian scripts. A test on a dataset of considerable size shows promising recognition rates: 97.29% for Devnagari and 96.34% for Bangla.

关键词： Handwriting recognition Humans Character recognition pattern recognition Keyboards computer vision Writing Job design Feature extraction Algorithm design and analysis

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Automatic recognition of printed Oriya script

Automatic recognition of printed Oriya script

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International Conference on Document Analysis and recognition

作者： B.B. Chaudhuri U. Pal M. Mitra Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India

ISBN: (纸本)0769512631

The paper deals with an optical character recognition system for printed Oriya, a popular Indian script. The development of OCR for this script is difficult because a large number of characters have to be recognized. In the proposed system, the digitized document image is first passed through preprocessing modules like skew correction, line segmentation, zone detection, word and character segmentation, etc. These modules have been developed by combining some conventional techniques with some newly proposed ones. Next, individual characters are recognized using a combination of stroke and run-number based features, along with features obtained from the concept of a water reservoir. The feature detection methods are simple and robust. A prototype of the system has been tested on a variety of printed Oriya material, and currently achieves 96.3% character level accuracy on average.

关键词： Character recognition Optical character recognition software Image segmentation Water resources Reservoirs computer vision Robustness Prototypes Materials testing System testing

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Cognitive Science and Artificial Intelligence 1

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丛书名： SpringerBriefs in Applied Sciences and Technology

1000年

作者： Sasikumar Gurumoorthy Bangole Narendra Kumar Rao Xiao-Zhi Gao

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An approach for stemming in symbolically compressed Indian language imaged documents

An approach for stemming in symbolically compressed Indian l...

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International Conference on Document Analysis and recognition

作者： U. Garain A.K. Datta Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots, and thereby improving the overall retrieval efficiency. This paper presents an algorithm for stemming in the context of document image retrieval system. The algorithm assumes that the documents are symbolically compressed and stemming has been attempted in the compressed domain itself. Experiments have been conducted on Indian language imaged documents for which efficient OCR still remains a challenging task. Results obtained from a set 150 document images (in Bangla script, the second most popular script in the Indian sub-continent) consisting of about 12K word show a promising performance of the proposed approach.

关键词： Image coding Image retrieval Optical character recognition software Information retrieval Internet Image storage computer vision pattern recognition Search engines Character recognition

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Automatic identification of English, Chinese, Arabic, Devnagari and Bangla script line

Automatic identification of English, Chinese, Arabic, Devnag...

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International Conference on Document Analysis and recognition

作者： U. Pal B.B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India

In a general situation, a document page may contain several scriptforms. For optical character recognition (OCR) of such a document page, it is necessary to separate the scripts before feeding them to their individual OCR systems. An automatic technique for the identification of printed Roman, Chinese, Arabic, Devnagari and Bangla text lines from a single document is proposed. Shape based features, statistical features and some features obtained from the concept of a water reservoir are used for script identification. The proposed scheme has an accuracy of about 97.33%.

关键词： Water resources Reservoirs Optical character recognition software Shape Water storage Probability computer vision pattern recognition Optical devices Fractals

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Script line separation from Indian multi-script documents

Script line separation from Indian multi-script documents

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International Conference on Document Analysis and recognition

作者： U. Pal B.B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India

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%.

关键词： Natural languages Optical character recognition software Shape Optical filters computer vision pattern recognition Writing Read only memory Character generation

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