2010 · 18 citations · 5 references
ComputingComputer ScienceComputer VisionMachine LearningMachine VisionFeature DetectionImage ClassificationObject RecognitionPattern RecognitionShape AnalysisCoin ClassificationCoin ImageryLight Reflection PropertiesReflection EffectRotation InvarianceShape Invariance
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.
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A New Approach to Coin Recognition using Neural Pattern Analysis
R. Bremananth, B. Balaji, M. Sankari et al. · 2006 · 58 citations
A Robust Coin Recognition Method with Rotation Invariance
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Statictics of Gabor features for coin recognition
Linlin Shen, Sen Jia, Zhen Ji et al. · 2009 · 22 citations