Recognition of Simple and Conjunct Handwritten Malayalam Characters Using LCPA Algorithm
This paper mainly focuses on the recognition of both simple and conjunct handwritten characters in Malayalam, a South Indian language. The algorithm proposed recognizes these characters mainly based on the strokes and lines contained in them. Here the input is an image of handwritten Malayalam characters, which undergoes different phases of processing to produce an editable document of Malayalam characters in a predefined format as output. In this paper, detailed description of the methods for character identification is given. The whole OCR process is presented in three different modules: Pre-processing, Skeletonization and Recognition. In Pre-processing, the input image is scanned and subjected to line and character separation. In Skeletonization, the digital image is transformed into a set of original components. In Recognition, the characters are classified based on their features. The feature extraction of the characters is done by the analyzing the position and count of the horizontal and vertical lines. A classification of the simple and conjunct characters is also devised based on the count and position of the horizontal and vertical lines which make up those characters.
KeywordsMalayalam Optical Character Recognition Feature Extraction Wavelet Transform Neural Networks HLH Patterns
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