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Improving Accuracy for Authenticity Inspection of Brand Items Using Logo Region Detection Processing

Ryo Inoue, Tomio Goto, and Satoshi Hirano
Dept. of Computer Science, Nagoya Institute of Technology, Nagoya, Japan

Abstract—In recent years, manufacturing technology of counterfeit brand products has advanced, and it is becoming very difficult for humans to distinguish many counterfeit products. In this paper, we propose an inspection system using two image matching methods to realize authenticity inspection of logo parts of brand items by recognize those images. In the first experiment, we compare the similarity evaluation performance by NCC (Normalized Cross- Correlation) and POC (Phase-Only Correlation) using images of actual brand products. In the next experiment, we propose logo region detection processing using edge images as preprocessing of image matching with the aim of improving inspection accuracy of images containing many background components. Experimental results show that it is possible to separate genuine and fake more accurately by evaluating similarity by POC. Moreover, we confirmed that by adding the logo region detection processing, the background component of the image was reduced and highly accurate inspection was possible.

Index Terms—feature point matching, template matching, NCC, POC, Sobel filter

Cite: Ryo Inoue, Tomio Goto, and Satoshi Hirano, "Improving Accuracy for Authenticity Inspection of Brand Items Using Logo Region Detection Processing," Journal of Image and Graphics, Vol. 7, No. 3, pp. 68-75, September 2019. doi: 10.18178/joig.7.3.68-75

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