Probabilistic binary similarity distance for quick binary image matching
Adnan A. Y. Mustafa · IET Image Processing · 2018
Here, the author presents the gamma binary distance, an exceptional distance for measuring similarity between binary images. The gamma distance is a probabilistic pixel mapping measure that is a modification of the Hamming distance. Employing a probabilistic approach to image matching enables gamma to measure similarity more accurately than employing traditional binary distances. The author shows the advantage of employing the gamma distance for similarity measurement by comparing it to three of the most popular similarity distances used for binary image matching: correlation, sum of the absolute difference method, and mutual information. Results of extensive testing conducted on a large database are presented where the superiority of the gamma distance over other similarity distances is shown.