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Support Vector Machines (SVMs) have successfully been used in recognizing printed characters. In the present work, we have used this classification technique to recognize handwritten characters. Recognition of handwritten characters is a difficult task owing to various writing styles of individuals. A scheme for offline handwritten Gurmukhi character(More)
Text line segmentation is extremely important phase of OCR. Overlapped lines, skewed lines and connected components make the problem of line segmentation more complicated in Gurumukhi handwritten documents. The existence of these problems in handwritten text documents declines the performance of OCR system. In this paper, we present a technique to solve(More)
In this paper, we have discussed the new method for Line Segmentation of Handwritten Hindi text. The method is based on header line detection, base line detection and contour following technique. No preprocessing like skew correction, thinning or noise removal has been done on the data. The purpose of this paper is three fold. Firstly, we explained by(More)
Horizontally overlapping lines are normally found in printed newspapers of any Indian script. Along with these overlapping lines few other broken components of a line (strip) having text less than a complete line are also found in text. The horizontally overlapping lines and other strips make it very difficult to estimate the boundary of a line leading to(More)
Offline handwritten character recognition has been a frontier area of research for the last few decades under pattern recognition. Recognition of handwritten characters is a difficult task owing to various writing styles of individuals. A scheme for offline handwritten Gurmukhi character recognition based on k-NN classifier is presented in this paper. The(More)
In this paper, we describe the line, word, character and top character segmentation for printed Hindi text in Devanagari script. And also describe the line and word segmentation for printed text in Gurmukhi script. A performance of 100% at line level, approximately 100% at word level, 99% at character level, and 97% at top character level for Devanagari(More)
Optical Character Recognition (OCR) is a process to recognize the handwritten or printed scanned text with the help of a computer. Segmentation is very important stage of any text recognition system. The problems in segmentation can lead to decrease in segmentation rate and hence recognition rate. A good segmentation technique can improve the recognition(More)
Grading of writers based on their handwriting is a complex task mainly because of various writing styles of different individuals. In this paper, we have attempted grading of writers based on offline Gurmukhi characters written by them. Grading has been accomplished based on statistical measures of distribution of points on the bitmap image of characters.(More)
Optical Character Recognition (OCR) is an essential part of Document Analysis System. Among few phases of an OCR system, segmentation is an important phase. After preprocessing phase, it is necessary to segment the text into lines, words and characters before the recognition of text. Segmentation is one of the most important and challenging tasks in a(More)