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
收藏
页码：731 / 740
页数：10
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