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A modified approach of identification and tracking of heart boundary from MRI image sequences

A modified approach of identification and tracking of heart ...

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IEEE Region 10 International Conference TENCON

作者： B.B. Chaudhuri Sucharita Mitra Arindam Bhattacharya Sutama Mitra Saugata Dutta Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India Department of Computer Science and Engineering Heritage Institute of Technology India

In the present work, a robust algorithm for automatic identification and segmentation of heart portion from cardiac Magnetic Resonance video Image (MRI) is presented. At first, an outline has been generated to get the region of interest (ROI) by employing the moving object criterion, which eventually reduces the processing time significantly. In the next step, Expectation Maximization (EM) algorithm is used to segment the grey scale images into 5 distinct regions. This is done to make them more suitable for further processing and easy to use in the developed software. Finally Level set algorithm added with automatic contour generation module is used for tracking the exact heart boundary to segment it out from the rest of the image. This algorithm gives equally persistent result for both long axis and shot axis cardiac MRI data consisting of a movie (in AVI format) containing 32 separate frames of grayscale images.

关键词： Heart Magnetic resonance imaging Image sequences Image segmentation Deformable models Shape Level set Biomedical imaging Noise shaping Gray-scale

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Rural cardiac healthcare system-A scheme for developing countries

Rural cardiac healthcare system-A scheme for developing coun...

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IEEE Region 10 International Conference TENCON

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

A simple, easy to implement and low cost mobile health(m-health) solution using general packet radio service (GPRS) of globally extended cellular mobile network for economically deprived countries is described in this paper. According to different statistical surveys, heart disease is a major health burden throughout the world but more importantly the third world countries like India, Pakistan, Bangladesh. We consider here a telecardiology system, where the ECG images captured by mobile camera are sent using Multimedia Massage Service (MMS) to a data extraction and processing unit. This unit can extract digitized data from those images, which may be restored as database in a dedicated server and also analyzed by an inbuilt knowledgebase as well as a rough decision generating system. Ultimately, the system will generate an automated report that will suggest the primary treatment and preventive measures to be taken by the patient. The report will be sent back to the patient by Short Message Service (SMS) through the same mobile system. The main advantage of the system is that it will not require constant monitoring or presence of a doctor at the initial stage. The ECG of the patient with critical abnormality or unknown abnormality will be directly sent to the doctorpsilas mobile and intimation will also be sent to the patient site directly. The extreme popularity of mobile phone with camera in the third world countries makes this architecture practically realizable.

关键词： Medical services Electrocardiography Cameras Data mining Costs Packet radio networks Ground penetrating radar Cellular networks Cardiac disease Multimedia systems

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Multi-Oriented English Text Line Extraction Using Background and Foreground Information

Multi-Oriented English Text Line Extraction Using Background...

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IAPR International Workshop on Document Analysis Systems, DAS

作者： Partha Pratim Roy Umapada Pal Josep Lladós Fumitaka Kimura Computer Vision Center Universitat Autònoma Barcelona Bellaterra Spain Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India Graduate School of Engineering Mie University Mie Japan

In graphical documents (map, engineering drawing), artistic documents etc. there exist many printed materials where text lines are not parallel to each other and they are multi-oriented and curve in nature. For the OCR of such documents we need to extract individual text lines from the documents. Extraction of individual text lines from multi-oriented and/or curved text document is a difficult problem. In this paper, we propose a novel method to extract individual text lines from such document pages and the method is based on the foreground and background information of the characters of the text. To take care of background information, water reservoir concept is used here. In the proposed scheme at first, individual components are detected and grouped into 3-character clusters using their inter-component distance, size and positional information. Applying concept of graph, initial 3-character clusters are merged to have larger cluster group. Using inter-character background information, orientations of the extreme characters of a larger cluster are decided and based on these orientation, two candidate regions are formed from the cluster. Finally, with the help of these candidate regions, individual lines are extracted. From the experiment, we obtained encouraging result.

关键词： Data mining Water resources Reservoirs Optical character recognition software Image segmentation Character recognition Text analysis Information analysis pattern analysis pattern recognition

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Convex hull based approach for multi-oriented character recognition from graphical documents

Convex hull based approach for multi-oriented character reco...

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International Conference on pattern recognition

作者： Partha Pratim Roy Umapada Pal Josep Llados Fumitaka Kimura Computer Vision Center Universitat Autònoma De Barcelona Bellaterra Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Mie Japan

ISBN: (纸本)9781424421749

In this paper, we present a scheme towards recognition of English character in multi-scale and multi-oriented environments. Graphical document such as map consists of text lines which appear in different orientation. Sometimes, characters in a single word may follow a curvilinear way to annotate the graphical curve lines. For recognition of such multi-scale and multi-oriented characters a Support Vector Machine (SVM) based scheme is presented in this paper. The feature used here is invariant to character orientation. Circular ring and convex hull have been used along with angular information of the contour pixels of the character to make the feature rotation invariant. We tested our proposed scheme on two different datasets. Combining circular and convex hull feature we have obtained 96.73% and 99.56% accuracy in these two datasets.

关键词： Character recognition pattern recognition Support vector machines Frequency Text recognition Histograms Clocks Rivers Optical character recognition software Testing

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Offline handwritten Devanagari word recognition: An HMM based approach

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2nd International Conference on pattern recognition and Machine Intelligence, PReMI 2007

作者： Parui, Swapan Kumar Shaw, Bikash Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata 700108 India

ISBN: (纸本)3540770453

A hidden Markov model (HMM) for recognition of handwritten Devanagari words is proposed. The HMM has the property that its states are not defined a priori, but are determined automatically based on a database of handwritten word images. A handwritten word is assumed to be a string of several stroke primitives. These are in fact the states of the proposed HMM and are found using certain mixture distributions. One HMM is constructed for each word. To classify an unknown word image, its class conditional probability for each HMM is computed. The classification scheme has been tested on a small handwritten Devanagari word database developed recently. The classification accuracy is 87.71% and 82.89% for training and test sets respectively. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Word processing

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Handwritten bangla compound character recognition using gradient feature

Handwritten bangla compound character recognition using grad...

引用

10th International Conference on Information Technology, ICIT 2007

作者： Pal, U. Wakabayashi, T. Kimura, F. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India Graduate School of Engineering Mie University 1577 Kurimamachiya-cho Tsu Mie Japan

ISBN: (纸本)0769530680

recognition of handwritten characters of Indian script is difficult because of the presence of many complex shaped compound characters (cluster characters) as well as variability involved in the writing style of different individuals. This paper deals with recognition of off-line Bangla handwritten compound characters using Modified Quadratic Discriminant Function (MQDF). The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2 X 2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. A Roberts filter is then applied on the normalized image to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the frequencies of these directions are down sampled using Gaussian filter to get 392 dimensional feature vectors. Using 5-fold cross validation technique we obtained 85.90% accuracy from a dataset of Bangla compound characters containing 20,543 samples. © 2007 IEEE.

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A system for off-line oriya handwritten character recognition using curvature feature

A system for off-line oriya handwritten character recognitio...

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10th International Conference on Information Technology, ICIT 2007

ISBN: (纸本)0769530680

In this paper we present a system towards the recognition of off-line Oriya handwritten characters. Since most of the Oriya characters have curve-like stroke, we use curvature feature for the recognition purpose. To get the feature, at first, the input image is size normalized and segmented into 4949 blocks. Curvature is then computed using bi-quadratic interpolation method and quantized into 3 levels according to concave, linear and convex regions. Next direction of gradient is quantized into 32 levels with π/16 intervals, and strength of the gradient is accumulated in each of the 32 directions and in each of the 3 curvature levels of every block. A spatial resolution is made to get 77 blocks from 4949 blocks and a directional resolution is made to get 8 directions from 32 directions. Using curvature features for 3 levels we get 1176 (77 blocks × 8 directions × 3 levels) dimensional features. Finally using principal component analysis we reduce the dimension 1176 to 392 and this 392 dimensional feature vector is fed to a quadratic classifier for recognition. We tested 18190 samples of Oriya handwritten samples and obtained 94.60% accuracy from our proposed system. © 2007 IEEE.

关键词： Principal component analysis

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Direction Code Based Features for recognition of Online Handwritten Characters of Bangla

Direction Code Based Features for Recognition of Online Hand...

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International Conference on Document Analysis and recognition

作者： U. Bhattacharya B.K. Gupta S. Parui Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In the present article, we describe a novel direction code based feature extraction approach for recognition of online Bangla handwritten basic characters. We have implemented the proposed approach on a database of 7043 online handwritten Bangla (a major script of the Indian subcontinent) character samples, which has been developed by us. This is a 50-class recognition problem and we achieved 93.90% and 83.61% recognition accuracies respectively on its training and test sets.

关键词： Character recognition Handwriting recognition Spatial databases pattern recognition Histograms Shape Testing Personal digital assistants computer vision Feature extraction

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A Two Stage recognition Scheme for Handwritten Tamil Characters

A Two Stage Recognition Scheme for Handwritten Tamil Charact...

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International Conference on Document Analysis and recognition

作者： U. Bhattacharya S.K. Ghosh S. Parui Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

India is a multilingual multiscript country with more than 18 languages and 10 different major scripts. Not enough research work towards recognition of handwritten characters of these Indian scripts has been done. Tamil, an official as well as popular script of the southern part of India, Singapore, Malaysia, and Sri Lanka has a large character set which includes many compound characters. Only a few works towards handwriting recognition of this large character set has been reported in the literature. Recently, HP Labs India developed a database of handwritten Tamil characters. In the present paper, we describe an off-line recognition approach based on this database. The proposed method consists of two stages. In the first stage, we apply an unsupervised clustering method to create a smaller number of groups of handwritten Tamil character classes. In the second stage, we consider a supervised classification technique in each of these smaller groups for final recognition. The features considered in the two stages are different. The proposed two-stage recognition scheme provided acceptable classification accuracies on both the training and test sets of the present database.

关键词： Character recognition Handwriting recognition Spatial databases pattern recognition Testing Speech recognition computer vision Natural languages Clustering methods Personal communication networks

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SVM Based Scheme for Thai and English Script Identification

SVM Based Scheme for Thai and English Script Identification

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International Conference on Document Analysis and recognition

作者： S. Chanda O.R. Terrades U. Pal Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India Computer Vision Center Universitat Authnòma de Barcelona Barcelona Spain

In some Thai documents, a single text line of a document page may contain both Thai and English scripts. For the optical character recognition (OCR) of such a document page it is better to identify, at first, Thai and English script portions and then to use individual OCR system of the respective scripts on these identified portions. In this paper, a SVM based method is proposed for identification of word-wise printed English and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of the individual character group combining different character features obtained from structural shape, profile, component overlapping information, topological properties, water reservoir concept etc. Based on the experiment on 6110 data we obtained 99.36% script identification accuracy from the proposed scheme.

关键词： Support vector machines Optical character recognition software Support vector machine classification computer vision Optical network units Structural shapes Water resources Reservoirs Neural networks pattern recognition

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