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http://dx.doi.org/10.5391/JKIIS.2014.24.5.504

Image Recognition Based on Nonlinear Equalization and Multidimensional Intensity Variation  

Cho, Yong-Hyun (School of Information Tech. Eng., Catholic Univ. of Daegu)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.24, no.5, 2014 , pp. 504-511 More about this Journal
Abstract
This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.
Keywords
Image Recognition; Nonlinear Histogram Equalization; Intensity Variation; Similarity Criterion; Normalized Cross-correlation Coefficient;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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