Title: A new interval type 2 fuzzy-based pixel wise information extraction for face recognition

Authors: Sudesh Yadav; Virendra P. Vishwakarma

Addresses: University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, Sector 16-C, New Delhi, India ' University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, Sector 16-C, New Delhi, India

Abstract: A new efficient and robust approach based on pixel wise information extraction and fuzzy logic concept is presented here for the application of face recognition (FR). As all the pixels of an individual face image do not participate equally in identifying a face image from a given set of classes. Therefore, in this paper, we use a new interval type 2 fuzzy based pixel wise information extraction (NIntTy2FPIE) on input face images for computing the pixel wise association of individual pixels of a face image in a given dataset. Next, computational cost is reduced by principle component analysis (PCA) and classification is done using a variant of nearest neighbour classifier (NNC), called k-NNC. Experiments performed on ORL, Yale and Georgia Tech and AR face database show that our method outperforms with many state-of-art methods and also proves that the proposed method with k-NNC is much more efficient and robust.

Keywords: face recognition; interval type 2 fuzzy logics; membership function; classification approaches.

DOI: 10.1504/IJAPR.2018.094812

International Journal of Applied Pattern Recognition, 2018 Vol.5 No.3, pp.171 - 190

Received: 18 Sep 2017
Accepted: 15 Apr 2018
Published online: 23 Sep 2018 *

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