ISOLATED HANDWRITTEN ARABIC NUMERALS RECOGNITION USING THE K-NEAREST NEIGHBOR AND THE HIDDEN MARKOVMODEL CLASSIFIERS

被引：0

作者：

El Kessab, Badre-eddine ^{[1
]}

Daoui, Cherki ^{[1
]}

Bouikhalene, Belaid ^{[1
]}

Salouan, Rachid ^{[1
]}

机构：

[1] Fac Sci & Technol, Lab Informat Proc & Decis Support, BP 523, Beni Mellal, Morocco

来源：

FACTA UNIVERSITATIS-SERIES MATHEMATICS AND INFORMATICS | 2015年 / 30卷 / 05期

关键词：

K-Nearest Neighbor; HiddenMarkov Model;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper deals with a recognition system of handwritten Arabic numerals extracted to the MNIST standard database (Arabic numerals). This system is composed of three main phases: the pre-processing of numerals followed by the extraction of primitives with the zoning method in order to convert each image into a vector number, which is nothing other than a piece of information extracted from this numeral just to differentiate the others. Finally, our recognition system will end with a classification phase using two methods: the K-nearest neighbours (K-NN) and HiddenMarkovModel (HMM). This work has achieved a recognition rate of approximately 82 of success.

引用

页码：731 / 740

页数：10

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