Title: Face detection and recognition system based on hybrid statistical, machine learning and nature-based computing

Authors: R. Vinodini; M. Karnan

Addresses: Department of Computer Science, Mother Teresa Women's University, Kodaikanal, Tamil Nadu, India ' Aringer Anna College of Engineering and Technology, Palani, Tamil Nadu, 624616, India

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.

Keywords: face detection; recognition; PCA; support vector machine; SVM; ant colony optimisation; ACO; segmentation; feature extraction; classification.

DOI: 10.1504/IJBM.2022.119543

International Journal of Biometrics, 2022 Vol.14 No.1, pp.3 - 19

Received: 20 May 2019
Accepted: 04 Nov 2019

Published online: 09 Dec 2021 *

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