Detection of imitation from authentic shoe apparel using integrated image processing techniques

Abstract

Counterfeit protection plays an essential role in the business industry. A manufacturer and seller of these products gain income by misleading consumers into buying replicas and Class A products. This holds true for designer clothes, bags, jewelry, shoes, etc. Counterfeit products are produced with the intent to take advantage of the superior value of the original product. In this paper, the researchers propose a method of detecting counterfeit shoes, specifically Stan Smith and Gazelle of Adidas Company. The shoes will be captured in specific areas such as midsole, insole, quarter, tongue, sole, and heel cap where Adidas logos or trademark is present. This study uses image processing techniques such as Circular Hough Transform, A-KAZE, and Optical Character Recognition. The results showed that the methods were successful in determining an authentic shoe from a non-authentic shoe. It was determined that the system has an accuracy of 93% and 96%, while having an error rate of 7% and 4% for Gazelle and Stan Smith respectively. Furthermore, a true positive rate of 100% for both shoes implies that whenever a shoe is predicted to be authentic it is actually authentic. On another note, a false positive rate of 12.3% and 7.4% for Gazelle and Stan Smith respectively implies how often is it predicted to be authentic when it is actually not authentic.