An Enhanced Template Matching Technique for Recognition of Telugu Script

Abstract: Feature extraction and classification processes while developing Optical Character Recognition (OCR) systems involve massive computations and quite expensive especially for South Indian scripts. Multiple combinations of vowels and consonants along with its modifiers led to generation of huge number of classes with respect to character recognition systems. The feature extraction and classification of characters from such huge number of classes in south Indian language OCRs remains as a non-trivial problem. This paper proposes a technique for feature extraction and classification of Telugu handwritten script based on customized template matching approach with the support of caching technique for better performance. The technique of caching is implemented using main database with a cache database maintaining the frequently used character templates for set of all character templates. The XML database is used for defining the classes for various character templates and the class representations are provided using a novel class structure designed based on XML tags. The proposed system exhibits the recognition efficiency on our own test dataset with an accuracy of 93.55% for handwritten characters.