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 clas...
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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.
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 automat...
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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.
This paper aims at automatic recognition of online handwritten mathematical expressions written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. A ...
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A document page may contain two or more different scripts. For Optical Character recognition (OCR) of such a document page, it is necessary to separate different scripts before feeding them to their individual OCR sys...
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ISBN:
(纸本)0769519601
A document page may contain two or more different scripts. For Optical Character recognition (OCR) of such a document page, it is necessary to separate different scripts before feeding them to their individual OCR system. In this paper an automatic scheme is presented to identify text lines of different Indian scripts from a document. For the separation task at first the scripts are grouped into a few classes according to script characteristics. Next feature based on water reservoir principle, contour tracing, profile etc. are employed to identify them without any expensive OCR-like algorithms. At present, the system has an overall accuracy of about 97.52%.
This paper deals with an Optical Character recognition system for printed Urdu, a popular Indian script. The development of OCR for this script is difficult because (i) a large number of characters have to be recogniz...
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ISBN:
(纸本)0769519601
This paper deals with an Optical Character recognition system for printed Urdu, a popular Indian script. The development of OCR for this script is difficult because (i) a large number of characters have to be recognized (ii) there are many similar shaped characters. In the proposed system individual characters are recognized using a combination of topological, contour and water reservoir concept based features. The feature detection methods are simple and robust. A prototype of the system has been tested on printed Urdu characters and currently achieves 97.8% character level accuracy on average.
To take care of variability involved in the writing style of different individuals in this paper we propose a robust scheme to segment unconstrained handwritten Bangla texts into lines, words and characters. For line ...
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ISBN:
(纸本)0769519601
To take care of variability involved in the writing style of different individuals in this paper we propose a robust scheme to segment unconstrained handwritten Bangla texts into lines, words and characters. For line segmentation, at first, we divide the text into vertical stripes. Stripe width of a document is computed by statistical analysis of the text height in the document. Next we determine horizontal histogram of these stripes and the relationship of the minimal values of the histograms is used to segment text lines. Based on vertical projection profile lines are segmented into words. Segmentation of characters from handwritten word is very tricky as the characters are seldom vertically separable. We use a concept based on water reservoir principle for the purpose. Here we, at first, identify isolated and connected (touching) characters in a word. Next touching characters of the word are segmented based on the reservoir base area points and structural feature of the component.
Optical Character recognition (OCR) systems show poor performance while processing documents like old books or newspapers, Xerox materials, faxed documents, etc. Such documents are considered as degraded documents. On...
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