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IJSTR >> Volume 8 - Issue 8, August 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Implementation Of Template Matching, Fuzzy Logic And K Nearest Neighbor Classifier On Philippine Banknote Recognition System

[Full Text]

 

AUTHOR(S)

Rodel Emille T. Bae, Edwin R. Arboleda, Adonis Andilab, Rhowel M. Dellosa

 

KEYWORDS

Currency Recognition System, Fuzzification, Fuzzy Logic, Image Processing, KNN, Inference Method, MatLab, Mamdami,

 

ABSTRACT

Currency recognition system is one of the most marked research topics at present. Lots of variety of applications triggered the researchers for a study like this. Monetary transaction is natural in human being for its daily transactions. The need to use an artificial intelligence to come up with determination and classifications of banknote may contribute to the improvement of artificial intelligence applications. An attempt was made in this study to apply image processing, fuzzy logic and K Nearest Neighbor for the improvement on the limitations of the existing currency recognition systems. The study has is divided into two parts: a template matching technique for feature extraction and comparison of accuracy between fuzzy logic algorithm and KNN based on the information gathered by the first part. Thus by implementing the Image Processing and FLC in the MATLAB with the help of MATLAB programming and fuzzy logic toolbox, recognition of Philippine currency will be more accurate. KNN shows it flaws to identify the features resulting to big errors unlike the first method.

 

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