| Autor: |
Benchaou, Soukaina, Nasri, M'Barek, Melhaoui, Ouafae El |
| Předmět: |
|
| Zdroj: |
International Journal of Image & Graphics; Jul2018, Vol. 18 Issue 3, pN.PAG-N.PAG, 13p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
