Feature Extraction for a Class of Uneven Illumination Image
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    Abstract:

    Changes in lighting are unavoidable and they have a big effect on the way the object looks. It makes a challenge to find a robust local invariant feature descriptor for these uneven illumination images. Most of approaches to feature extraction are based on the premise of that the color image should be converted to grayscale. This paper presents a new approach that it introduces the color independent components based on the Kubelka-Munk model instead of using the gray space to detect the corners. It uses multi-scale Harris corner detection to show the feature of the image, so more details were demonstrated. Experimental results support the potential of the proposed approach.

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吴金杰,杨翠荣,杨勇,庞全.一类光照不均图像的特征提取方法.计算机系统应用,2011,20(12):79-82,78

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  • Received:April 06,2011
  • Revised:May 06,2011
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