Coin Recognition Method Based on SIFT Algorithm
Jing Xu, Gongliu Yang, Yuanyuan Liu, Jingjia Zhong · 2017
Coin recognition is one of the prime important activities for modern banking and currency processing systems in which machine vision is widely used. The technique at the heart of such systems is object recognition in a digital image. Although it has high recognition speed, the traditional method of coin recognition can not recognize the coins with similar sizes. This paper presents a method based on SIFT(scale invariant feature transform) algorithm for coin recognition. SIFT algorithm can handle the issues of rotations, scaling and illumination in a digital image. Therefore it can solve the problem about distinguishing the coins which have approximate size. In experiments, we compare the performances of Chinese coin recognition with our proposed method and the traditional method(based on size). The results demonstrate the feasibility and effectiveness of our approach.