Mendeley
TY  _  JOUR
ID  -  1401062439347
TI  -  Providing a Face Recognition System with an Optimal Selection of Features Based on the Cuckoo Optimization Algorithm
JO  -  Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran
JA  -  ES
LA  -  fa
SN  -  16823745
AU  -  Hoseini Farnaz
AU  -  Sepehrzadeh Hamed
AD  -  گروه مهندسی کامپیوتر، دانشگاه فنی و حرفه‌ای، تهران، ایران
AD  -  استادیار، گروه مهندسی کامپیوتر، دانشگاه فنی و حرفه‌ای، تهران، ایران
AD  -  گروه مهندسی کامپیوتر، موسسه آموزش عالی و غیر انتفاعی شهریار آستارا، آستارا، ایران
Y1  -  2024
PY  -  2024
VL  -  1
IS  -  
SP  -  12
EP  -  20
KW  -  Face recognition
KW  -   feature optimization
KW  -   cuckoo optimization algorithm
KW  -   optimization algorithm
DO  -  
N2  -  Face recognition is a pattern recognition process that is specifically performed on faces. Face recognition has many applications in identifying credit cards, security systems, and other cases. Creating a face recognition system with high accuracy is a big challenge that has been the focus of various researchers in recent years. The feature extraction process and classification are two important issues in diagnosis systems that can play a significant role in increasing the accuracy of diagnosis. Considering this issue, in this study, taking into account the combined features and optimizing the cuckoo algorithm, a method to improve the accuracy of face recognition is proposed. In the presented method, seven features are extracted from the images in the database, and then by obtaining the feature vector, the steps related to feature selection are performed using the cuckoo algorithm. The proposed method has been implemented with MATLAB software and compared with other methods. The evaluation results show that the proposed method was able to perform the detection on the images of ORL and FDBB databases with 93.00% and 95.12% accuracy, respectively. The result obtained for this evaluation criterion has a higher value than other compared methods.
UR  - rimag.ir/en/Article/39347
L1  - rimag.ir/en/Article/Download/39347
ER  -  
