Evaluation of Features Extraction and Classification Techniques for Offline Handwritten Tifinagh Recognition (Global Journal of Computer Science and Technology, 2016)
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.
Keywords: handwritten recognition; tifinagh characters; extraction features (statistical; structural and global transformation); classification (HMM; MLP; SVM)