Histogram-based stereo matching under varying illumination conditions

Il Lyong Jung, Jae Young Sim, Chang-Su Kim

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    A histogram-based matching algorithm for stereo images captured under different illumination conditions is proposed in this work. The cumulative histogram of an image represents the ranks of relative pixel brightness, which are robust to illumination changes. Therefore, we design the matching cost based on the similarity of the cumulative histograms of stereo images. As an optional mode, the proposed algorithm can evaluate the histograms for foreground objects and the background separately to alleviate occlusion artifacts. To determine the disparity of each pixel, the proposed algorithm adaptively aggregates matching costs based on the color similarity and the geometric proximity of neighboring pixels. Then, it refines false disparities at occluded pixels using more reliable disparities of non-occluded pixels. Experimental results demonstrate that the proposed algorithm provides higher quality disparity maps than the conventional methods under varying illumination conditions.

    Original languageEnglish
    Title of host publication2012 IEEE Visual Communications and Image Processing, VCIP 2012
    DOIs
    Publication statusPublished - 2012
    Event2012 IEEE Visual Communications and Image Processing, VCIP 2012 - San Diego, CA, United States
    Duration: 2012 Nov 272012 Nov 30

    Publication series

    Name2012 IEEE Visual Communications and Image Processing, VCIP 2012

    Other

    Other2012 IEEE Visual Communications and Image Processing, VCIP 2012
    Country/TerritoryUnited States
    CitySan Diego, CA
    Period12/11/2712/11/30

    Keywords

    • Stereo matching
    • color similarity
    • histogram
    • illumination variation

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition

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