Gaussian Weighted Histogram Intersection for License Plate Classification

The conventional histogram intersection (HI) algorithm computes the intersected section of the corresponding color histograms in order to measure the matching rate between two color images. Since this algorithm is strictly based on the matching between bins of identical colors, the final matching rate could easily be affected by color variation caused by various environment changes. In this paper, a Gaussian weighted histogram intersection (GWHI) algorithm is proposed to facilitate the histogram matching via taking into account matching of both identical and similar colors. The weight is determined by the distance between two colors. The GWHI is applied to license plate classification. Experimental results demonstrate that the proposed algorithm produces a much lower intra-class distance and a much higher inter-class distance than previous HI algorithms for images which are captured under various illumination conditions.

• Type: Conference
• Year: 2006
• Where: ICPR
• Authors: Huaifeng Zhang, Qiang Wu, Wenjing Jia, Xiangjian He
• Keywords: Computer Vision, Conventional Histogram Intersection, Final Matching Rate, ICPR 2006, Weighted Histogram Intersection