Cuneiform symbols recognition by support vector machine (SVM)

Abstract

     Cuneiform character recognition represents a complex problem in pattern recognition as result of problems that related to style of this type of writing and the diversity of its features according to distortion and shadows problems. This research proves  that  polygon approximation  method is an optimal feature extra action method , which has been adopted for recognition task compeer with elliptic Fourier descriptor,  according to the  achieved  high  accuracy recognition results after applying multiple classes of  support vector machine classifier along with depending on its discriminate functions .This work is applied by using two Data set , the first one contains 320 images of cuneiform symbols patterns for evaluate the optimal feature extraction method. The second contains 240 images of cuneiform characters to evaluate the recognition system, agents training dataset  consists of 2D four triangular patterns.