Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi Research Article, J Comput Eng Inf Technol Vol: 2 Issue: 1
Comparison of Neuro-fuzzy Networks for Classification Fingerprint Images
| O. Assas1,2*, A. Aijimi2, I. Boudrah2, M. Bouamar3 and K. Benmahammed4 | |
| 1Department of Electronics, University of Batna, Algeria | |
| 2Department of Computer Science, University of M’sila, Algeria | |
| 3Department of Electronics, University of M’sila, Algeria | |
| 4Department of Computer Engineering, Minnesota University, Duluth, MN, USA | |
| Corresponding author : Assas Ouarda Department of Computer Science, University of M’sila, M’sila, Algeria Tel: +213794732238 E-mail: assas_warda@yahoo.fr |
|
| Received: January 01, 2013 Accepted: March 20, 2013 Published: March 28, 2013 | |
| Citation: Assas O, Aijimi A, Boudrah I, Bouamar M, Benmahammed K (2013) Comparison of Neuro-fuzzy Networks for Classification Fingerprint Images. J Comput Eng Inf Technol 2:1. doi:10.4172/2324-9307.1000104 |
Abstract
Comparison of Neuro-fuzzy Networks for Classification Fingerprint Images
Classification means to assign a given fingerprint to one of the existing classes already recognized in the literature. A search over all the fingerprints in the database takes a long time, so thegoal is to reduce the search time and computational complexity by choosing an appropriate subset of database for search. Classifying a fingerprint images is and will remain a challenging problem in pattern recognition, due to the minimal interclass variability and maximal intra-class variability.
