HOG and Zone Base Features for Handwritten Malayalam Character Classification
M S Pooja · International Journal for Research in Applied Science and Engineering Technology · 2020
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.Considering that the zone based feature used in this research is simply the pixel count in each zone, future research may be performed to extract more statistical properties on each zone.Future works may also focus on rotation free feature extraction for Malayalam character classification.