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IJSTR >> Volume 8 - Issue 10, October 2019 Edition



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

Website: http://www.ijstr.org

ISSN 2277-8616



Coffee Type Classification Using Gray Level Co-Occurrence Matrix Feature Extraction And The Artificial Neural Network Classifier

[Full Text]

 

AUTHOR(S)

Alvin M. Castillo, Raymond D. Aradanas and Edwin R. Arboleda, Andy A. Dizon and Rhowel M. Dellosa

 

KEYWORDS

ANN, Classifier, Coffee, Image Processing, GLCM

 

ABSTRACT

This paper is focused on determining the species of a coffee bean using the GLCM or the Gray Level Co-Occurrence Matrix method with the help of ANN or the Artificial Neural Network. This research is done to make a new method in determining the species of coffee bean in different parts of Cavite (Arabica, Excelsa, and Robusta). The image processing techniques that the author will use will be simulated in order the classify the species of the coffee bean that will be used. The coffee bean features based on the GLCM are the Contrast, Energy, Cluster Shade and Sum of Square Variance that will be extracted from 120 training images and 60 testing images. Using the ANN classifier, it will categorize the coffee bean based on the said parameters for GLCM. Using ANN classification, the scores of 95.31% were achieved. In conclusion, the study showed that image processing can effectively determine the quality of the coffee bean varieties.

 

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