The recognition of handwritten characters remains one of challenging task in character recognition problems. The
variations created by each person in writing the characters affect the character recognition result. Many studies have been
performed to increase the performance of Malayalam character recognition. The efforts are to extract the best feature for
classification or to get the best classifier for classification. In this study, HOG feature and zoning based feature is be used to
classify Malayalam Characters. The performance of both features will be compared for classifying Malayalam character by
using SVM classifier. The result showed that HOG feature is able to show higher accuracy as compared to the simple zone based
feature. The best accuracy for HOG is achieved by using binary input. On the other hand, despite its simplicity zone based
feature is able to achieve accuracy by using skeleton input
