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Izvorni znanstveni članak
https://doi.org/10.2498/cit.1001427

An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients

Virendra P. Vishwakarma
Sujata Pandey
M. N. Gupta

Puni tekst: engleski, pdf (2 MB) str. 53-67 preuzimanja: 810* citiraj
APA 6th Edition
P. Vishwakarma, V., Pandey, S. i Gupta, M.N. (2010). An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients. Journal of computing and information technology, 18 (1), 53-67. https://doi.org/10.2498/cit.1001427
MLA 8th Edition
P. Vishwakarma, Virendra, et al. "An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients." Journal of computing and information technology, vol. 18, br. 1, 2010, str. 53-67. https://doi.org/10.2498/cit.1001427. Citirano 25.06.2019.
Chicago 17th Edition
P. Vishwakarma, Virendra, Sujata Pandey i M. N. Gupta. "An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients." Journal of computing and information technology 18, br. 1 (2010): 53-67. https://doi.org/10.2498/cit.1001427
Harvard
P. Vishwakarma, V., Pandey, S., i Gupta, M.N. (2010). 'An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients', Journal of computing and information technology, 18(1), str. 53-67. doi: https://doi.org/10.2498/cit.1001427
Vancouver
P. Vishwakarma V, Pandey S, Gupta MN. An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients. Journal of computing and information technology [Internet]. 2010 [pristupljeno 25.06.2019.];18(1):53-67. doi: https://doi.org/10.2498/cit.1001427
IEEE
V. P. Vishwakarma, S. Pandey i M.N. Gupta, "An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients", Journal of computing and information technology, vol.18, br. 1, str. 53-67, 2010. [Online]. doi: https://doi.org/10.2498/cit.1001427

Sažetak
In this paper, a novel approach for illumination normalization under varying lighting conditions is presented. Our approach utilizes the fact that discrete cosine transform (DCT) low-frequency coefficients correspond to illumination variations in a digital image. Under varying illuminations, the images captured may have low contrast; initially we apply histogram equalization on these for contrast stretching. Then the low-frequency DCT coefficients are scaled down to compensate the illumination variations. The value of scaling down factor and the number of low-frequency DCT coefficients, which are to be re-scaled, are obtained experimentally. The classification is done using k-nearest neighbor classification and nearest mean classification on the images obtained by inverse DCT on the processed coefficients. The correlation coefficient and Euclidean distance obtained using principal component analysis are used as distance metrics in classification. We have tested our face recognition method using Yale face database B. The results show that our method performs without any error (100% face recognition performance) even on the most extreme illumination variations. There are different schemes in the literature for illumination normalization under varying lighting conditions, but no one is claimed to give 100% recognition rate under all illumination variations for this database. The proposed technique is computationally efficient and can easily be implemented for real time face recognition system.

Hrčak ID: 59514

URI
https://hrcak.srce.hr/59514

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