JAIS (Journal of Applied Intelligent System)
Vol 7, No 2 (2022): Journal of Applied Intelligent System

GLCM Based Locally Feature Extraction On Natural Image

Edi Faisal (Universitas Dian Nuswantoro)
Agung Nugroho (Universitas Dian Nuswantoro)
Ruri Suko Basuki (Universitas Dian Nuswantoro)
Suharnawi Suharnawi (Universitas Dian Nuswantoro)



Article Info

Publish Date
07 Sep 2022

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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Journal Info

Abbrev

JAIS

Publisher

Subject

Description

Journal of Applied Intelligent System (JAIS) is published by LPPM Universitas Dian Nuswantoro Semarang in collaboration with CORIS and IndoCEISS, that focuses on research in Intelligent System. Topics of interest include, but are not limited to: Biometric, image processing, computer vision, ...