DETEKSI EKSUDAT PADA CITRA RETINA MENGGUNAKAN MEAN SHIFT SEGMENTATION DAN ADAPTIVE THRESHOLDING

ABSARI, TRIMONA and Erwin, Erwin (2020) DETEKSI EKSUDAT PADA CITRA RETINA MENGGUNAKAN MEAN SHIFT SEGMENTATION DAN ADAPTIVE THRESHOLDING. Undergraduate thesis, Sriwijaya University.

	Text RAMA_56201_09011181520117_00292017101.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) | Request a copy
	Text RAMA_56201_09011181520117_0029017101_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (9MB) | Request a copy
Preview	Text RAMA_56201_09011181520117_0029017101_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (2MB) | Preview
	Text RAMA_56201_09011181520117_0029017101_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (617kB) | Request a copy
	Text RAMA_56201_09011181520117_0029017101_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (417kB) | Request a copy
	Text RAMA_56201_09011181520117_0029017101_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_56201_09011181520117_0029017101_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (10kB) | Request a copy
	Text RAMA_56201_09011181520117_0029017101_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (91kB) | Request a copy
	Text RAMA_56201_09011181520117_0029017101_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (233kB) | Request a copy

Abstract

Diabetic retinopathy is the retinal damage of people with diabetes mellitus. Diabetic retinopathy suffer can vision to decline until the suffer is blind for a long time. Diabetes disease is characterized by the appearance of several disorders. Abnormalities that accur in the retina one of which is describe by exudate. Exudate is the main sign of diabetic retinopathy caused by leakage and dilation of blood vessels around the retina. Exudate in the form of dots or spots that have a yellowish color with various shapes and fairly high contrast. In this final project research the authors conducted the exudate detection study using Mean Shift Segmentation and Adaptive Thresholding to diagnose diseases of the retina. In thir study the authors used the STARE dataset. The first convert the original image into a RGB to Luv, eliminate fine lines in the image by using mean shift segmentation. after that the image will be converted to grayscale. Then, it will be converted into a green channel. Then, the image will be detected in the exudate candidate area using illumination correction. Enhance the contrast of retinal images with contrast adjustments. Next, removal of the optical disk. After remove the optic disk the detection of exudate is done by segmentation using adaptive thresholding. then the removal of small objects that can interfere with exudate detection. Then, to remove small holes and to refine the contour morphology closing is used. Next, use ROI to remove the outline on the retina. Using this method, getting the average result for accuracy of 97.87% and spesificity of 96.71%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	DiabetiK Retinopati, Optick Disk, Adaptive Thresholding, Mean Shift Segmentation
Subjects:	T Technology > T Technology (General) > T351-385 Mechanical drawing. Engineering graphics T Technology > T Technology (General) > T351-385 Mechanical drawing. Engineering graphics > T355 Structural drawing
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 7629 not found.
Date Deposited:	22 Sep 2020 03:48
Last Modified:	22 Sep 2020 03:48
URI:	http://repository.unsri.ac.id/id/eprint/33654

Actions (login required)

View Item