Tifinagh Printed Character Recognition through Structural Feature Extraction

Abstract

In this paper a system for the recognition of printed Tifinagh characters is presented. It is divided into three main steps: preprocessing, feature extraction, and classification. Image quality is enhanced through preprocessing which are: binarization, normalization and thinning. Then the image is given to a proposed structural feature extracting algorithm where the character is divided into several geometrically sample shapes which are segments, then transformed into an undirected graph with unique coordinate of all nodes. The character is classified by matching the graph of the character and its counterpart graph which is generated from the images in the IRCAM database using an efficient spectral graph matching algorithm. Experimental results and analysis are accomplished by the use of 3267 random characters to test the effectiveness. The system shows good results in term of accuracy and CPU time.