Isolated Handwritten Malayalam Character Recognition Using HLH Intensity Patterns

Abstract

Recently Indian Handwritten character recognition is getting much more attention and researchers are contributing a lot in this field. But Malayalam, a South Indian language has very less works in this area and needs further attention. This paper focuses on an efficient algorithm for recognizing the handwritten Malayalam characters. Malayalam OCR is a complex task owing to the various character scripts available and more importantly the difference in ways in which the characters are written. The dimensions are never the same and may be never mapped on to a square grid unlike English characters. Here we propose an algorithm which can accept the scanned image of handwritten characters as input and to produce the editable Malayalam characters in a predefined format as output without applying any resizing or skeletonization methods but still can produce much accurate results. Characters are grouped in to different classes based on their HLH intensity patterns. These patterns are separated from the image and fed for recognition. Algorithm is tested for 4 sets of samples ranging 661 letters in the noiseless environment and produces an accuracy of 88%.