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http://dx.doi.org/10.9717/kmms.2019.22.12.1404

An Efficient Image Matching Scheme Based on Min-Max Similarity for Distorted Images  

Heo, Young-Jin (Dept. of IT Engineering, Sookmyung Women's University)
Jeong, Da-Mi (Dept. of IT Engineering, Sookmyung Women's University)
Kim, Byung-Gyu (Dept. of IT Engineering, Sookmyung Women's University)
Publication Information
Journal of Korea Multimedia Society / v.22, no.12, 2019 , pp. 1404-1414 More about this Journal
Abstract
Educational books commonly use some copyrighted images with various kinds of deformation for helping students understanding. When using several copyrighted images made by merging or editing distortion in legal, we need to pay a charge to original copyright holders for each image. In this paper, we propose an efficient matching algorithm by separating each copyrighted image with the merged and edited type including rotation, illumination change, and change of size. We use the Oriented FAST and Rotated BRIEF (ORB) method as a basic feature matching scheme. To improve the matching accuracy, we design a new MIN-MAX similarity in matching stage. With the distorted dataset, the proposed method shows up-to 97% of precision in experiments. Also, we demonstrate that the proposed similarity measure also outperforms compared to other measure which is commonly used.
Keywords
Image Processing; Image Matching; Similarity Measure; MIN-MAX Similarity; Distorted Images;
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Times Cited By KSCI : 4  (Citation Analysis)
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