Pattern Matching Model for Recognition of Stone Inscription Characters

Abstract

Abstract As there are countless significant works done for handwritten character recognition, very meager effort has been reported for inscription characters especially for Tamil stone inscriptions. The real challenge faced in handling stone inscription is dataset collection and foreground and background discrimination. Till present days, the archeological department follows traditional way of capturing, preserving and deciphering stone inscriptions which is manual, more time consuming and need expert assistance. Hence digitized recognition is essential and efficient pattern matching algorithm is needed to be developed to deal with variations in shape and size of complex structured characters present in Tamil stone inscriptions. In this paper, an automated character recognition by pattern matching approach is developed, where character features were extracted by using pattern matching algorithm that helps achieving good recognition rate. Recognition of ancient Tamil stone inscriptions characters and finding their corresponding contemporary Tamil character is done by Image-based Character Pattern Identification (ICPI) system. Modified Speeded Up Robust Feature with Bag of Grapheme (MSURF-BoG) algorithm is implemented to detect the strongest key points from the input character with different orientations. These key point features were created for training the image as a model called Bag of Grapheme (BoG) with code word creation. Hence unsupervised key point features were extracted and pattern matching is performed. 11th century Tamil stone inscriptions were taken as samples which has 7 vowels and 17 consonants, totally 24 characters were used. Here samples with different orientation from each 24 character were used for training the system. The proposed system is evaluated by recognition accuracy which is reported for character wise at the maximum of 96%.