Illumination preprocessing of color face based on inverse-intensity chromaticity space
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Abstract:
An image preprocessing method based on the inverse-intensity chromaticity space(IICS)theory is proposed to solve the problem that the color information is sensitive to illumination condition in a color face recognition method. This method evenly divides the image into blocks. Then,the pixels in each block are converted to a 2 dimensional data set in the IICS,which takes a linear distribution,and the illumination color of this block is estimated from this data set. After the illumination colors of all the blocks are derived,a color histogram is computed based on the estimated colors,and the colors are merged according to the histogram. Finally,illumination condition of the image is rectified to the canonical illumination using the estimated colors and the diagonal model,and this rectified image is used for recognition. Experiments on the AR and FERET face databases show that the robustness to illumination variation is effectively improved,and the recognition accuracy is increased by introducing the illumination preprocessing scheme into a color face recognition method.
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Project Supported:
Supported by Fundamental and Advanced Research Project of Chongqing Municipality of China(cstc2013jcyjA40028)；Science and Technology Research Project of Chongqing Education Department(KJ400518)；Application Development Project of Chongqing Municipality of China(cstc2013yykfC60006)and Foundation of Chongqing Normal University(13XLB012).
