Face detection and recognition system based on hybrid statistical, machine learning and nature-based computing Online publication date: Thu, 09-Dec-2021
by R. Vinodini; M. Karnan
International Journal of Biometrics (IJBM), Vol. 14, No. 1, 2022
Abstract: Face detection becomes an important task carried out in biometric-based security system and identification application. This paper presents the detailed investigations on different methods suffering from accuracy and computational complexity used for the face detection and recognition. The face detection and recognition with high performance ratio for face detection and recognition is achieved in the methods investigated. The reduction of complexity can happen at any stages of the face recognition like preprocessing, segmentation, feature extraction, recognition, etc. The proposed method presented in this paper is based on principal component analysis (PCA), support vector machine (SVM), K-nearest neighbour (KNN) and ant colony optimisation (ACO). The detail investigation of the proposed method is made and is compared with the existing methods. From the results, it can be observed that the proposed method is better in performance when compared to other methods.
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