GLCM Based Locally Feature Extraction On Natural Image

Edi Faisal, Agung Nugroho, Ruri Suko Basuki, Suharnawi Suharnawi

Abstract


GLCM is a feature extraction method that uses statistical analysis using a gray scale. Contrast, correlation, energy and entropy are feature features whose value will be sought as the basis for finding the threshold which can then be used to find the threshold value in image segmentation. In this study, a local-based GLCM method is used where the image that has been made into grayscale will be divided into 16 parts of the same size. Each section will look for the value of its GLCM features, namely Contrast, correlation, energy and entropy. The calculation of these four features will be applied to 16 parts of the grayscale image, which can then be used to find the threshold value. The results of the four features in the calculation with an angle of 0o are the contrast value = 0.0080, correlation = 0.619, energy : 0.00160 and entropy : 0.05591.

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DOI: https://doi.org/10.33633/jais.v7i2.6569

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Journal of Applied Intelligent System (e-ISSN : 2502-9401, p-ISSN : 2503-0493) is published by Department of Informatics Universitas Dian Nuswantoro Semarang and IndoCEISS.

  

 

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