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Frequency-plane analysis of normal and pathological ECG signals for disease identification

Journal of Medical Engineering and Technology 2005年第5期29卷 219-227页

作者： Mitra, S. Mitra, M. Chaudhuri, B.B. Department of Applied Physics Faculty of Technology University of Calcutta 92 APC Road Kolkata - 700009 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata - 700 108 India

In this paper a frequency plane analysis of both normal and diseased ECG signals is performed specifically for disease identification. Image processing techniques are used to develop an automated data acquisition package of 12 lead ECG signals from paper records. A regeneration domain is also developed to check the captured pattern with the original wave shape. A QRS complex detector with an accuracy level ∼98.4% in up to 30% signal to noise level is developed. Discrete Fourier transform (DFT) is performed to obtain the frequency spectrum of every ECG signal. Some interesting amplitude and phase response properties of chest lead V2, V3, V4, V6 and limb lead I, II, III, AVL, AVF are seen. Both amplitude and phase properties are different for normal and diseased subjects and can serve an important role in disease identification. A statistical analysis of amplitude property is carried out to show that this property is significantly different for normal and diseased subjects. © 2005 Taylor & Francis.

关键词： Electrocardiography

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A Novel Approach to Skew Detection and Character Segmentation for Handwritten Bangla Words

A Novel Approach to Skew Detection and Character Segmentatio...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： A. Roy T.K. Bhowmik S.K. Parui U. Roy Department of Computer and System Sciences Visva Bharati University Santiniketan India Embassy Golf Link IBM Global Services Private Limited Bangalore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Character segmentation is a necessary preprocessing step for character recognition in many handwritten word recognition systems. The most difficult case in character segmentation is the cursive script. Fully cursive nature of Bangla handwriting, the natural skewness in words poses some challenges for automatic character segmentation. In this article a novel approach to skew detection, correction as well as character segmentation has been presented for handwritten Bangla words as a test case. Segmenting points are extracted on the basis of some patterns observed in the handwritten words. With these segmenting points a graphical path (hereafter referred to as a candidate path) has been constructed. The handwritten words contain some consistent and also inconsistent skewness. Our algorithm can cope with both types of skewness at a time. Further the method is so direct that with the help of a candidate path one can handle both skew correction and segmentation successfully. the algorithm has been tested on a database prepared for laboratory use. The method yields fairly good results for this database.

关键词： Image segmentation Character recognition Optical character recognition software computer vision pattern recognition Testing Databases Algorithm design and analysis Writing Handwriting recognition

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Optimal sub-shape models by minimum description length

Optimal sub-shape models by minimum description length

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Conference on computer vision and pattern recognition (CVPR)

作者： G. Langs P. Peloschek H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Department of Clinical Radiology Vienna Medical University Vienna Austria

Active shape models are powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowledge in an efficient and gainful way. However, due to the linearity of PCA, non-linearities like rotations or independently moving sub-parts in the data can deteriorate the resulting model considerably. Although non-linear extensions of active shape models have been proposed and application specific solutions have been used, they still need a certain amount of user interaction during model building. In this paper the task of building/choosing optimal models is tackled in a more generic information theoretic fashion. In particular, we propose an algorithm based on the minimum description length principle to find an optimal subdivision of the data into sub-parts, each adequate for linear modeling. This results in an overall more compact model configuration. Which in turn leads to a better model in terms of modes of variations. The proposed method is evaluated on synthetic data, medical images and hand contours.

关键词： Active shape model Biomedical imaging Principal component analysis computer vision Linearity Polynomials pattern recognition computer graphics Radiology Image processing

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An approach to a rough set decision system for classification of different heart diseases

An approach to a rough set decision system for classificatio...

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AMSE International Conference on Modelling and Simulation, MS'2004

作者： Mitra, S. Mitra, M. Chattopadhya, S. Chaudhuri, B.B. Department of Applied Physics Faculty of Technology University of Calcutta India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India JIS College of Engineering Kalyani India

In this paper a rule based rough set decision system for development of a disease inference engine is described. For this purpose an off-line data acquisition system of paper electrocardiogram (ECG) records are developed using image processing techniques. A QRS detector is developed for detection of R-R interval from ECG waves. After detection of this R-R interval the P and T waves are detected based on syntactic approaches and different time-plane features are extracted from every ECG signals. From a knowledgebase which is developed from the feedback of different reputed cardiologists and consultation of different medical books the essential time plane features for ECG interpretation have been selected. Finally, a rule-based roughest decision system is generated for the development of an inference engine for disease identification from these time-plane features.

关键词： Inference engines

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Identification of embedded mathematical expressions in scanned documents

Identification of embedded mathematical expressions in scann...

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International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri A.R. Chaudhuri Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Department of Computer Science & Engineering Jadavpur University Kolkata India

Efficient extraction of mathematical expressions is considered as an important pre-processing step to apply existing OCR systems to convert scientific papers into their electronic format. In this correspondence, a technique for extracting embedded (or in-line) expressions has been presented. The proposed method for expression extraction initially invokes an existing OCR to recognize the input document. Several features including word n-grams (a statistical analysis of a corpus of scientific documents reveals that the word level n-gram profile for sentences containing embedded expressions is quite different from that of the sentences without any expression) are computed on sentence level to spot sentences containing expressions. Expression zones are pin pointed by exploiting OCR inability to handle expressions and by using some common typographical aspects followed in typing mathematical expressions. Experimental results on a considerable size of dataset show high efficiency of the proposed technique.

关键词： Optical character recognition software Text recognition Character recognition pattern recognition computer vision computer science Statistical analysis Embedded computing Engines Matrix converters

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A multiple-classifier system for recognition of printed mathematical symbols

A multiple-classifier system for recognition of printed math...

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International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri R.P. Ghosh Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Student Department of Computer Science & Engineering MCKV Institute of Engineering Howrah West Bengal India

This paper deals with recognition of printed mathematical symbols. A group of classifiers arranged hierarchically is used to achieve robust recognition of the large number of symbols appearing in expressions. The classifier used at the top level employs stroke-based classification technique to recognize some of the frequently occurring symbols. The second level uses three classifiers to recognize the rest of the expression symbols. Different combination techniques have been attempted to integrate the second level classifiers to achieve high recognition accuracy. Experiment shows that the proposed approach is quite robust for recognition of a large number of symbols appearing in various expressions.

关键词： pattern recognition Robustness Feature extraction Shape computer vision computer science Handwriting recognition Testing Character recognition Typesetting

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Detection of QRS complex of ECG signals from square-derivative curve

Modelling, Measurement and Control C

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Modelling, Measurement and Control C 2004年第1-2期65卷 15-27页

作者： Mitra, S. Mitra, M. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata 700108 India Department of Applied Physics University College of Science and Tech. University of Calcutta Kolkata 700009 India

An approach to QRS complex detection based on the selection of maximum area zone of square derivative curve is presented in this paper. At first the ECG signals are being extracted from paper ECG records by an automated data acquisition system which has been developed by using image processing techniques. Then the QRS complex of each ECG signal is detected even in the presence of power line interference and baseline drift to calculate the sampling period for further analysis in frequency plane for disease identification. A very high accuracy level (∼ 99.4%) has been achieved in detection of QRS complex by this method.

关键词： computer vision

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Robust occupancy detection from stereo images

Robust occupancy detection from stereo images

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International Conference on Intelligent Transportation

作者： B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA

Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.

关键词： Robustness Magnetic heads Vehicle crash testing Sensor systems Stereo vision Layout Statistical analysis Support vector machines Support vector machine classification Vehicle detection

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Preface

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3316卷 V-VI页

作者： Pal, Nikhil R. Kasabov, Nikola Mudi, Rajani K. Pal, Srimanta Parui, Swapan K. Indian Statistical Institute Electronics and Communications Sciences Unit 203 B. T. Road Calcutta India Private Bag 92006 Auckland New Zealand Jadavpur University Department of Instrumentation and Electronics Engineering Salt-lake Campus Calcutta India Indian Statistical Institute Computer Vision and Pattern Recognition Unit 203 B. T. Road Calcutta India

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Classifiability based omnivariate decision trees

Classifiability based omnivariate decision trees

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International Joint Conference on Neural Networks (IJCNN)

作者： Y. Li M. Dong Machine Vision and Pattern Recognition Laboratory Department of Computer Science Wayne State University Detroit MI USA

Decision trees represent a simple and powerful method of induction from labeled examples. Univariate decision trees consider the value of a single attribute at each node, leading to the splits that are parallel to the axes. In linear multivariate decision trees, all the attributes are used and the partition at each node is based on a linear discriminate (a hyperplane). Nonlinear multivariate decision trees are able to divide the input space arbitrarily based on higher order parameterizations of the discriminate, though one should be aware of the increase of the complexity and the decrease in the number of examples available as moves further down the tree. In omnivariate decision trees, the decision node may be univariate, linear, or nonlinear. Such architecture frees the designer from choosing the appropriate tree type for a given problem. In this paper, we propose to do the model selection at each decision node based on a novel classifiability measure when building omnivariate decision trees. The classifiability measure captures the possible sources of misclassification with relative ease and is able to accurately reflect the complexity of subproblems at each node. The proposed approach does not require the time consuming statistic tests at each node and therefore does not suffer from as high computational burden as typical model selection algorithm. Our simulation results over several data sets indicate that our approach can achieve at least as good classification accuracy as statistical tests based model select algorithms, but in much faster speed.

关键词： Classification tree analysis Decision trees Testing Shape Machine vision pattern recognition Laboratories computer science Buildings Statistical analysis

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