Categorization of Persian Detached Handwritten Letters Using Intelligent Combinations of Classifiers

Journal of Advances in Computer Research

شناسنامه علمی شماره، دوره 8، شماره 4 - شماره پیاپی 30، بهمن 2017، صفحه 13-21   

نویسندگان

Hossein Sadr^{* 1، 2، 3}؛ Mojdeh Nazari Solimandarabi^{2، 3}؛ Mahsa Mirhosseini Moghadam³

¹Department of Computer Engineering, Parand Branch, Islamic Azad University, Parand, Iran

²Young Researchers and Elite Club, Lahijan Branch, Islamic Azad University, Lahijan, Iran

³Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran

چکیده

Abstract—detecting optical characters is the main responsibility to convert printed documents and manuscripts to digital format. In this article, detecting Persian handwritten letters by using the combination of classifiers and features were assessed, hence geometric and statistical sections' features were used. In order to detect each letter, we divide it into two parts; the major and the minor parts. Then, we present some features for them. Preprocess algorithm prepare the possibility to unify dimension features for multiple words and deliver to classifier for detecting . We can get the hierarchy classification by separating the letters. After that, the optimal answer will be reached by using GA method of different SVM, ML and KNN classifications.
Extraction algorithm of needed features was proved by using the evaluation of the basis of PCA. Empirical results represent classification of 94.3 and 92 accuracy in simple and multiple parts in 20 times repetition, respectively.
eywords— Classifiers' Combination, Optical Character recognition, Persian handwritten, Reducing feature.

کلیدواژه‌ها

Classifiers' Combination؛ Optical Character recognition؛ Persian handwritten؛ Reducing feature