Affiliation:
1. Laboratory MATSI, Faculty of Sciences, University Mohammed First, Oujda 60000, Morocco
Abstract
Handwriting, printed character recognition is an interesting area in image processing and pattern recognition. It consists of a number of phases which are preprocessing, feature extraction and classification. The phase of feature extraction is carried out by different techniques; zoning, profile projection, and ameliored Freeman. The high number of features vector can increase the error rate and the training time. So, to solve this problem, we present in this paper a new method of selecting attributes based on the evolution strategy in order to reduce the feature vector dimension and to improve the recognition rate. The proposed model has been applied to recognize numerals and it obtained a better results and showed more robustness than without the selection system.
Publisher
World Scientific Pub Co Pte Lt
Subject
Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献