International Journal of Computer Theory and Engineering

Abstract

People start learning to read and write during the early stage of education. As years pass by they may have acquired good reading and writing skills. It may not be difficult for them to read any kind of either printed or handwritten characters. Most people have no problem in reading any kind of light prints or heavy prints, upside down prints, prints of different fonts and styles, handwritten whether it is neatly or sloppily written. But Computers may find difficultly in deciphering many kinds of printed characters which is of different fonts and styles or handwritten characters. To evolve a panacea to this problem human brains have been indulging in various research activities. This paper is a humble attempt for the recognition of handwritten Malayalam (a South Indian Language) characters. In our study we have classified the connected characters into 3 categories. Here we propose an algorithm which uses the inveterate characteristic features to recognize these characters with perceptive accuracy by utilizing the intensity variations in the way in which they may be written. This algorithm recognizes the antediluvian script of Malayalam characters which are connected in nature. Here the input is a 24-bit bmp image which can be enscribed using the Light pen. The output is editable version of the recognized Malayalam characters. In our study we have classified the connected characters into 3 categories. The algorithm is tested for 3 sets of samples ranging 402 letters in noiseless environment and produces accuracy of 94%.