No abstract

Currency recognition system is one of the fast growing research fields under image processing. This paper proposes a novel method for Indian currency recognition. Our proposed approach identifies denomination by extracting features like Center Numeral, Shape, RBI Seal, Latent Image and Micro Letter. Principal Component Analysis is used to reduce the dimensions and a similarity based classifier is constructed to predict test sample. Results are also validated by constructing models using classifier implemented using WEKA and testing with unseen samples not considered in feature extraction. Our study demonstrated that center numeral results in an accuracy of 100% with all family of currencies.

The determination of the currency denomination is an issue in paper currency recognition system. This paper proposes a robust method to recognize the paper currency using the pattern matching. In the proposed algorithm a similarity measure is used to classify the currency based on the similarity of the extracted features. To evaluate the performance of the proposed method experiments were conducted over 200 of currencies of different denominations. On performing the experiment the proposed method gives 97% accuracy.

No abstract

No abstract