Improved Object Recognition using Wavelet Transform & Histogram Equalization in the variable illumination 


Vol. 13,  No. 2, pp. 287-292, Apr.  2006
10.3745/KIPSTD.2006.13.2.287


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  Abstract

There are two problems associated with the existing principal component analysis, which is regarded as the most effective in object recognition technology. First, it brings about an increase in the volume of calculations in proportion to the square of image size. Second, it gives rise to a decrease in accuracy according to illumination changes. In order to solve these problems, this paper proposes wavelet transformation and histogram equalization. Wavelet transformation solves the first problem by using the images of low resolution. To solve the second problem, the histogram equalization enlarges the contrast of images and widens the distribution of brightness values. The proposed technology improves recognition rate by minimizing the effect of illumination change. It also speeds up the processing and reduces its area by wavelet transformation.

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[IEEE Style]

J. N. Kim, B. S. Jung, B. K. Kim, "Improved Object Recognition using Wavelet Transform & Histogram Equalization in the variable illumination," The KIPS Transactions:PartD, vol. 13, no. 2, pp. 287-292, 2006. DOI: 10.3745/KIPSTD.2006.13.2.287.

[ACM Style]

Jae Nam Kim, Byeong Soo Jung, and Byung Ki Kim. 2006. Improved Object Recognition using Wavelet Transform & Histogram Equalization in the variable illumination. The KIPS Transactions:PartD, 13, 2, (2006), 287-292. DOI: 10.3745/KIPSTD.2006.13.2.287.

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