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检索条件"机构=Computer Vision and Pattern Recognition"

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Aquaformer: Underwater Image Enhancement via Adaptive Transformer

Aquaformer: Underwater Image Enhancement via Adaptive Transf...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Harsh Bhandari Sarbani Palit Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Water causes degradation of quality in optical images captured underwater due to its physical properties of absorption and scattering. This degradation is further aggravated by the increase in water depth and the presence of contaminated water. Transformers in the vision domain have made a quantum leap in many vision tasks such as detection, and segmentation but yet to make any progress in enhancing degraded underwater images. We propose a transformer-based model named “Aquaformer” which makes four major contributions: an adaptive layer normalization, replacement of masked cyclic shift with symmetric padding in window partitioning, a novel aggregation mechanism, and an adjustable fusion approach. These succeed in making the model a very powerful one, producing significantly better performance compared to the latest state-of-the-art methods. Testing on multiple benchmark datasets, employing both quantitative and qualitative metrics, establishes its supremacy.

关键词： Degradation Water Adaptation models Scattering Benchmark testing Transformers Water pollution

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Neural network based word-wise handwritten script identification system for Indian postal automation

Neural network based word-wise handwritten script identifica...

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International Conference on Intelligent Sensing and Information Processing (ICISIP)

作者： K. Roy U. Pal B.B. Chaudhuri Indian Statistical Institute Computer Vision and Pattern Recognition Unit 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 piecewise projection method the destination address block (DAB), is at first segmented into lines and then into words. Using water reservoir concept we compute the busy-zone of the word. Finally, using matra/Shirorekha, water reservoir concept based feature, fractal based feature, etc. a neural network (NN) classifier is generated for word-wise Bangla and English scripts identification. Overall accuracy of the proposed system is at present 9 7.62%.

关键词： Neural networks Automation Natural languages Water resources Reservoirs Fractals Optical character recognition software computer vision pattern recognition USA Councils

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Segmentation of Bangla handwritten text into characters by recursive contour following

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

引用

International Conference on Document Analysis and recognition

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

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.

关键词： Image segmentation Optical character recognition software Hidden Markov models pattern recognition Image analysis Lattices computer vision Writing Feature extraction Linear programming

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OCR error detection and correction of an inflectional Indian language script

OCR error detection and correction of an inflectional Indian...

引用

International Conference on pattern recognition

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

This paper deals with an OCR error detection and correction technique for a highly inflectional language script like Bangla (a major Indian language). This is the first report of its kind. Using two separate lexicons of root words and suffixes, candidate root-suffix pairs of each input word are detected, their grammatical agreement are tested and the root/suffix part in which the error has occurred is noted. The correction is made on the corresponding error part of the input string by a fast dictionary access technique. To do so some alternative strings are generated for an erroneous word. Among the alternative strings, those satisfying grammatical agreement in root-suffix and also having smallest Levenstein-Damerau distance are finally chosen as the correct ones. The system has an accuracy of 75.61%.

关键词： Optical character recognition software Error correction Dictionaries computer errors Character recognition computer vision pattern recognition Testing Libraries Optical design

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Wavelet-based approach for writer identification in music score

Wavelet-based approach for writer identification in music sc...

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IEEE International Advance Computing Conference, IACC

作者： Debleena Das Sukalpa Chanda Partha Pratim Roy Umapada Pal Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479925735

Writer identification is a vibrant research field, though a lot of work has been done on writer identification on normal text, writer identification in music score sheet has not been addressed in that large scale. Here we propose a method to identify writers of music score sheets using Daubchies wavelet features along with SVM classifier. We have evaluated our proposed approach in a sub-set of CVC-MUSCIMA dataset. From the experiment on 140 score sheet images from 7 writers we obtained encouraging results.

关键词： Support vector machines Feature extraction Accuracy Conferences Training Wavelet transforms

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Segmentation of touching symbols for OCR of printed mathematical expressions: an approach based on multifactorial analysis

Segmentation of touching symbols for OCR of printed mathemat...

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International Conference on Document Analysis and recognition

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

This paper deals with segmentation and recognition of touching characters appearing in scanned mathematical expressions. The technique is based on multifactorial analysis that integrates several factors determining cut-positions in a touching character image. A predictive algorithm is developed for efficient selection of possible cut-positions for segmenting touching characters. Experiment has been carried out using a test-set of reasonable size and results show that a considerable improvement in recognition accuracy can be achieved with a modest increase in computations.

关键词： Optical character recognition software Image segmentation Character recognition pattern recognition Image analysis Image databases pattern analysis computer vision Prediction algorithms Testing

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CoCoNet: A Collaborative Convolutional Network applied to fine-grained bird species classification

CoCoNet: A Collaborative Convolutional Network applied to fi...

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International Conference on Image and vision Computing New Zealand, IVCNZ

作者： Tapabrata Chakraborti Brendan McCane Steven Mills Umapada Pal University of Otago Computer Vision and Pattern recognition Unit Indian Statistical Institute

The following topics are dealt with: convolutional neural nets; learning (artificial intelligence); image classification; computer vision; feature extraction; video signal processing; deep learning (artificial intelli... 详细信息

ISBN: (数字)9781728185798

ISBN: (纸本)9781728185804

关键词： Training Visualization Image recognition Collaboration computer architecture Birds Task analysis

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Automatic separation of words in multi-lingual multi-script Indian documents

Automatic separation of words in multi-lingual multi-script ...

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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 may contain more than one script forms. For such a document it is necessary to separate different script forms before feeding them to OCRs of individual script. In this paper an automatic word segmentation approach is described which can separate Roman, Bangla and Devnagari scripts present in a single document. The approach has a tree structure where at first Roman script words are separated using the 'headline' feature. The headline is common in Bangla and Devnagari but absent in Roman. Next, Bangla and Devnagari words are separated using some finer characteristics of the character set although recognition of individual character is avoided. At present, the system has an overall accuracy of 96.09%.

关键词： Optical character recognition software Natural languages computer vision Shape pattern recognition Tree data structures Character recognition Continents Cleaning Character generation

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A syntactic approach for processing mathematical expressions in printed documents

A syntactic approach for processing mathematical expressions...

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International Conference on pattern recognition

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

ISBN: (纸本)0769507506

We propose an approach for understanding mathematical expressions in printed documents. The overall approach is divided into three main steps: (i) detection of mathematical expressions in a document, (ii) recognition of the symbols present in the expression and (iii) arrangement of the recognized symbols. The detection of mathematical expressions is done through recognition of a few most common symbols and exploiting some structural features of the expressions. A hybrid of feature based and a template-based technique is used for the recognition of symbols. A two-pass approach is used for arrangement of the symbols. The first pass (scanning or lexical analysis) performs a micro-level examination of the symbols in order to identify the symbol groups occurring in them and to determine their categories or descriptors. The second pass (parsing or syntax analysis) processes the descriptors synthesized in the first pass, to determine the syntactic structure of the expression. A set of predefined rules guides the activities in both the passes. Experiments conducted using this approach on a large number of documents show high accuracy.

关键词： Optical character recognition software computer vision pattern recognition Performance analysis Equations Document handling Testing Books White spaces

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An OCR system to read two Indian language scripts: Bangla and Devnagari (Hindi)

An OCR system to read two Indian language scripts: Bangla an...

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International Conference on Document Analysis and recognition

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

An OCR system is proposed that can read two Indian language scripts: Bangla and Devnagari (Hindi), the most popular ones in the Indian subcontinent. These scripts, having the same origin in ancient Brahmi script, have many features in common and hence a single system can be modeled to recognize them. In the proposed model, document digitization, skew detection, text line segmentation and zone separation, word and character segmentation, character grouping into basic, modifier and compound character category are done for both scripts by the same set of algorithms. The feature sets and classification tree as well as the knowledge base required for error correction (such as lexicon) differ for Bangla and Devnagari. The system shows a good performance for single font scripts printed on clear documents.

关键词： Optical character recognition software Natural languages Error correction Character recognition Switches computer vision pattern recognition Cleaning Text recognition Writing

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