AUTOMATIC KLASIFIKASI CITRA MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION (LVQ) UNTUK MENGANALISIS PENYAKIT PADA RETINA

PUTRI, INDAH FRISILINA and Erwin, Erwin (2019) AUTOMATIC KLASIFIKASI CITRA MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION (LVQ) UNTUK MENGANALISIS PENYAKIT PADA RETINA. Undergraduate thesis, Universitas Sriwijaya.

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Abstract

The image on the retina is usually used for disease detection. Several types of retinal diseases are grouped from 50 images taken from the Retina STARE Project, namely Background Diabetic Retinopathy (BDR), Proliferative Diabetic Retinopathy (PDR), Coats, Choroidal Neovascularization (Choroidal), Retinis Disease (Retinis). Some retinal diseases have little resemblance so the suit is to be recognized. Zernike moment has 6 parameters that will be used as input in Learning Vector Quantization (LVQ). In recognizing the object of retinal disease combined by taking the closest distance value using the Learning Vector Quantization (LVQ) method. With the introduction of methods at least make it easier for someone to what disease is being suffered. The program was created using Microsoft Visual C# 2008. The test results showed an accuracy of 86% in recognizing the retinal disease.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Retinal Disease, Zernike Moment, Learning Vector Quantization (LVQ).
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 1457 not found.
Date Deposited:	21 Aug 2019 06:11
Last Modified:	21 Aug 2019 06:11
URI:	http://repository.unsri.ac.id/id/eprint/4715

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