Title: Weighted estimation for texture analysis based on Fisher discriminative analysis

Authors: Xiaoping Jiang; Chuyu Guo; Hua Zhang; Chenghua Li

Addresses: College of Electronics and Information Engineering, Hubei Key Laboratory of Intelligent Wireless Communications, South-Central University for Nationalities, Wuhan 430074, China ' College of Electronics and Information Engineering, Hubei Key Laboratory of Intelligent Wireless Communications, South-Central University for Nationalities, Wuhan 430074, China ' College of Electronics and Information Engineering, Hubei Key Laboratory of Intelligent Wireless Communications, South-Central University for Nationalities, Wuhan 430074, China ' College of Electronics and Information Engineering, Hubei Key Laboratory of Intelligent Wireless Communications, South-Central University for Nationalities, Wuhan 430074, China

Abstract: The traditional texture analysis methods only use relative contribution of each face area to mark the global similarity. For solving the problem of feature extraction which cause by local instead of global, weighted estimation for texture analysis (WETA) method based on the Fisher discriminative analysis (FDA) is proposed. First, local binary pattern (local binary pattern, LBP) or partial phase quantisation (local phase quantisation, LPQ) is used for image texture encoding. Then, the image is divided into local small pieces which are all equal and not overlap. The most discrimination axis, which are extracted from similarity space, are applied into texture analysis by FDA method, then the best solution through weight optimisation is given. Finally, experiments on two major general face databases (FERET and FEI) verify the effectiveness of the proposed method. The proposed method receives a recognition rate of 96% in LPQ and FERET combination. The experimental results show that compared with texture methods in other papers, the proposed method in this paper has obtained better recognition performance.

Keywords: face recognition; Fisher discriminative analysis; FDA; weighted estimation; texture coding.

DOI: 10.1504/IJICT.2018.095031

International Journal of Information and Communication Technology, 2018 Vol.13 No.4, pp.479 - 489

Received: 12 Dec 2015
Accepted: 07 Jan 2016

Published online: 21 May 2018 *

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