Interest point based face recognition using adaptive neuro fuzzy inference system

• Published in: Multimedia tools and applications Vol. 78; no. 16; pp. 22691 - 22710
• Main Author: Rejeesh, M R
• Format: Journal Article
• Language: English
• Published: New York Springer US 30.08.2019; Springer Nature B.V
• Subjects: Adaptive algorithms; Adaptive systems; Artificial neural networks; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Face recognition; Facial recognition technology; False alarms; Feature extraction; Fuzzy logic; Fuzzy systems; Genetic algorithms; Image detection; Multimedia Information Systems; Process parameters; Search algorithms; Special Purpose and Application-Based Systems; Swarm intelligence; Patch decision tree; Artificial bee colony algorithm (ABC); Adaptive genetic algorithm (GA); Adaptive neuro fuzzy inference system (ANFIS); Interest point
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-019-7577-5

In this paper, an efficient face recognition method using AGA and ANFIS-ABC has been proposed. At first stage, the face images gathered from the database are preprocessed. At Second stage, an interest point which is used to improve the detection rate consequently. The parameters used in the interest point determination are optimized using the Adaptive Genetic Algorithm. Finally using ANFIS, face images are classified by using extracted features. During the training process, the parameters of ANFIS are optimized using Artificial Bee Colony Algorithm (ABC) in order to improve the accuracy. The performance of the proposed ANFIS-ABC technique is evaluated using an ORL database with 400 images of 40 individuals, YALE-B database with 165 images of 15 individuals and finally with real time video the detection rate and false alarm rate is compared with proposed and existing methods to prove the system efficiency.