Efficient face recognition using frequency distribution curve matching

Document Type

Article

Publication Date

12-1-2012

Abstract

To develop an accurate and efficient face recognition system, a technique is proposed that preserves holistic as well as local facial details. It employs the cumulative frequency distribution curve (FDC) of the grey levels and their standard variance. Based on the FDC, a reduced space profile is produced, which is composed of three distinct segments. Each segment has its own associated error value defined in the range (0, 1). A decision is made by evaluating error values between the training and testing data sets independently for each segment in the FDC. A face is recognised accurately if there is conformance in all of the three segments; that is, the relevant error conditions are met simultaneously in all the segments. With one-shot training, the proposed technique is not only faster but also provides 14, 1.9 and 1.7% improvement in accuracy for the Yale, Olivetti Research Laboratory and pose, illumination and expression databases compared with other widely used face recognition techniques. © The Institution of Engineering and Technology 2012.

Identifier

84880012921 (Scopus)

Publication Title

Iet Image Processing

External Full Text Location

https://doi.org/10.1049/iet-ipr.2011.0565

ISSN

17519659

First Page

1161

Last Page

1196

Issue

8

Volume

6

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