Automatic Diagnosis System Identification of Coronary Heart Disease Using GLCM Feature Extraction and SVM Classification

Translated from Indonesian

ABSTRACT

Coronary heart is one of the heart diseases that very much affects humans. The cause of coronary heart disease is the accumulation of fat and cholesterol in the walls of blood vessels. The main cause of coronary heart disease due to an unhealthy human lifestyle. Poor diet, obesity and lack of exercise are the main causes of coronary heart disease. Narrowing of blood vessels is closely related to blood flow that occurs to the eye, especially the iris. So we need a method with a more efficient and inexpensive method to identify and identify heart disease from self by using iridology. The system is designed using Circle Hough Transformer (CHT) as automatic part detection, Gray Level Co-occurrence Matrix (GLCM) as feature extraction and Support Vector Machine (SVM) as classification. Tests have been carried out on 40 image data which obtained an identification success rate of 87.5%

Authors:

Vincentius Abdi Gunawan1),  Leonardus Sandy Ade Putra2),  Ignatia Imelda Fitriani3)

1)Teknik Informatika,Fakultas Teknik,Universitas Palangka Raya

2)Teknik Informatika, STMIK Palangka Raya

3)Fakultas Keguruan dan Ilmu Pendidikan, Universitas Palangka Raya

Source: Mulawarman Informatics: Scientific Journal of Computer Science Vol. 15, No. 1, February2013e-ISSN 2597-4963 and p-ISSN 1858-4853DOI: http://dx.doi.org/10.30872/jim.v15i1.2495

Download full abstract:  https://iridology-research.com/pdf/304923329.pdf