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A feature based face recognition technique using Zernike moments

Wiliem, Arnold, Madasu, Vamsi K., Boles, Wageeh W., & Yarlagadda, Prasad K.D.V. (2007) A feature based face recognition technique using Zernike moments. In Mendis, Priyan, Lai, Joseph, Dawson, Ed, & Abbas, Hussein (Eds.) RNSA Security Technology Conference 2007, 28 September 2007, Melbourne, Australia.

Abstract

In this paper, a face recognition approach using Zernike moments is presented for the main purpose of detecting faces in surveillance cameras. Zernike moments are invariant to rotation and scale and these properties make them an appropriate feature for automatic face recognition. A Viola-Jones detector based on the Adaboost algorithm is employed for detecting the face within an image sequence. Pre-processing is carried out wherever it is needed. A fuzzy enhancement algorithm is also applied to achieve uniform illumination. Zernike moments are then computed from each detected facial image. The final classification is achieved using a kNN classifier. The performance of the proposed methodology is compared on three different benchmark datasets. The results illustrate the efficacy of Zernike moments for the face recognition problem in video surveillance.

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ID Code: 12747
Item Type: Conference Paper
Additional Information: Some contents of this conference can be freely accessed online via the conference’s web page (see hypertext link).
Additional URLs:
Keywords: Face recognition, Zernike moments, Face Detection, Image Enhancement, K, NN classifier
ISBN: 9780975787397
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2007 Australian Homeland Research Centre and The authors
Deposited On: 29 Feb 2008
Last Modified: 29 Feb 2012 23:38

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