Title :
A Coin Recognition System with Rotation Invariance
Author :
Chen, Cai-ming ; Zhang, Shi-qing ; Chen, Yue-fen
Abstract :
This paper introduces a coin recognition method with rotation invariance. The rotation invariance feature is represented by the absolute value of Fourier coefficients of polar image of the coin on circles with different radii. Moreover, the Fourier approximation of the coin image is used to reduce the variations on surface of coin such as light reflection effect. Then coins can be distinguished by feeding those features into a multi-layered BP neural network. Finally the coin recognition experiments are given to show the effectiveness of the proposed method.
Keywords :
Feature extraction; Fourier transforms; Frequency; Image recognition; Image registration; Image segmentation; Magnetic materials; Neural networks; Pixel; Testing; BP neural network; Fourier transform; coordinate transform;
Conference_Titel :
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location :
Kaifeng, China
Print_ISBN :
978-1-4244-6595-8
Electronic_ISBN :
978-1-4244-6596-5
DOI :
10.1109/MVHI.2010.60
