2013 · 32 citations · 9 references
ComputingComputer ScienceArtificial IntelligenceComputer VisionMachine LearningObject RecognitionPattern RecognitionFeature AveragingRotation InvarianceShape Invariance
Coins are integral part of our day to day life. We use coins everywhere like grocery store, banks, buses, trains etc. So it becomes a basic need that coins can be sorted and counted automatically. For this it is necessary that coins can be recognized automatically. In this paper we have developed an ANN (Artificial Neural Network) based Automated Coin Recognition System for the recognition of Indian Coins of denomination `1, `2, `5 and `10 with rotation invariance. We have taken images from both sides of coin. So this system is capable of recognizing coins from both sides. Features are extracted from images using techniques of Hough Transformation, Pattern Averaging etc. Then, the extracted features are passed as input to a trained Neural Network. 97.74% recognition rate has been achieved during the experiments i.e. only 2.26 % miss recognition, which is quite encouraging.
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A Robust Coin Recognition Method with Rotation Invariance
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