A Comparative Study of Different Feature Extraction Techniques for Offline Malayalam Character Recognition

被引：10
|
作者：
Chacko, Anitha Mary M. O. [1 ]
Dhanya, P. M. [1 ]
机构：
[1] Rajagiri Sch Engn & Technol, Dept Comp Sci & Engn, Kochi, India
来源：
COMPUTATIONAL INTELLIGENCE IN DATA MINING, VOL 2 | 2015年 / 32卷
关键词：
Offline character recognition; Feature extraction; Neural networks;
D O I：
10.1007/978-81-322-2208-8_2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Offline Handwritten Character Recognition of Malayalam scripts have gained remarkable attention in the past few years. The complicated writing style of Malayalam characters with loops and curves make the recognition process highly challenging. This paper presents a comparative study of Malayalam character recognition using 4 different feature sets-Zonal features, Projection histograms, Chain code histograms and Histogram of Oriented Gradients. The performance of these features for isolated Malayalam vowels and 5 consonants are evaluated in this study using feedforward neural networks as classifier. The final recognition results were computed using a 5 fold cross validation scheme. The best recognition accuracy of 94.23 % was obtained in this study using Histogram of Oriented Gradients features.
引用
收藏
页码：9 / 18
页数：10
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