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http://dx.doi.org/10.3745/KIPSTD.2006.13D.2.287

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

Kim Jae-Nam (광주여자대학교 디지털영상그래픽학과)
Jung Byeong-Soo (남부대학교 디지털정보학과)
Kim Byung-Ki (전남대학교 전자컴퓨터정보통신공학과)
Publication Information
The KIPS Transactions:PartD / v.13D, no.2, 2006 , pp. 287-292 More about this Journal
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.
Keywords
Principal Component Analysis; Object Recognition; Wavelet; Histogram Equalization;
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