Quick probabilistic binary image matching: changing the rules of the game

Adnan A. Y. Mustafa

doi:10.1117/12.2237552

27 September 2016 Quick probabilistic binary image matching: changing the rules of the game

Adnan A. Y. Mustafa

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 997112 (2016) https://doi.org/10.1117/12.2237552
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

A Probabilistic Matching Model for Binary Images (PMMBI) is presented that predicts the probability of matching binary images with any level of similarity. The model relates the number of mappings, the amount of similarity between the images and the detection confidence. We show the advantage of using a probabilistic approach to matching in similarity space as opposed to a linear search in size space. With PMMBI a complete model is available to predict the quick detection of dissimilar binary images. Furthermore, the similarity between the images can be measured to a good degree if the images are highly similar. PMMBI shows that only a few pixels need to be compared to detect dissimilarity between images, as low as two pixels in some cases. PMMBI is image size invariant; images of any size can be matched at the same quick speed. Near-duplicate images can also be detected without much difficulty. We present tests on real images that show the prediction accuracy of the model.

Conference Presentation

Citation Download Citation

Adnan A. Y. Mustafa "Quick probabilistic binary image matching: changing the rules of the game", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997112 (27 September 2016); https://doi.org/10.1117/12.2237552

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