An Eigencharacter Technique for Offline-Tamil Handwritten Character Recognition

被引：0
|
作者：
Deepa, R. N. Ashlin [1 ]
Rao, R. Rajeswara [2 ]
机构：
[1] Gokaraju Rangaraju Inst Engn & Technol, Hyderabad 500090, Telangana, India
[2] Univ Coll Engn, Vizianagaram, Andhra Prades, India
来源：
PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND COMMUNICATION | 2017年 / 458卷
关键词：
Pattern recognition; Handwritten character recognition; Eigencharacter; Weightvector; Classification;
D O I：
10.1007/978-981-10-2035-3_51
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Accuracy in handwritten character recognition system is a challenge in the area of pattern recognition because of a variety of writing styles. Eigenface is a method that has been widely used in face recognition systems. This method is proposed in the field of handwritten character recognition, in this paper. Here, Eigencharacters are created from a 2-D training set of images and weight vectors are generated. These weight vectors are used as feature vectors for classification. The classification is performed using Euclidean Distance, k-NN and SVM classifiers. Experimental results proved that the proposed Eigencharacter method using Euclidean distance produced good classification accuracy.
引用
收藏
页码：495 / 505
页数：11
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