Evaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition

Abstract

This paper presents a review on different features extraction and classification methods for off-line handwritten Amazigh characters called Tifinagh recognition The features extraction methods are discussed based on Statistical Structural Global transformation and moments Although a number of techniques are available for feature extraction and classification but the choice of an excellent technique decides the degree of accuracy of recognition A series of experimentswere performed on AMHCD databaseallowing to evaluate the effectiveness of different techniques of extraction features based on Hidden Markov models Neural network and Support vector Machine classifiers The statistical techniques giveencouraging results