NDLI: Probabilistic binary similarity distance for quick binary image matching

Content Provider	IET Digital Library
Author	Mustafa, Adnan A. Y.
Abstract	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.
Starting Page	1844
Ending Page	1856
Page Count	13
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 10, Oct (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.1333
Journal	IET Image Processing
Publisher Date	2018-05-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Absolute Difference Method Binary Distances Binary Image Matching Computer Vision And Image Processing Technique Exceptional Distance Extensive Testing Gamma Binary Distance Hamming Distance Image Matching Image Recognition Mutual Information Probabilistic Approach Probabilistic Binary Similarity Distance Probabilistic Pixel Mapping Measure Probability Quick Binary Image Matching Similarity Measurement Statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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