Call for Paper - September 2018 Edition
IJCA solicits original research papers for the September 2018 Edition. Last date of manuscript submission is August 20, 2018. Read More

An Approach to Exudates Detection using Color Reference Segmentation in Retinal Fundus Image

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Diana Tri Susetianingtias, Sarifuddin Madenda, Rodiah
10.5120/ijca2016910692

Diana Tri Susetianingtias, Sarifuddin Madenda and Rodiah. An Approach to Exudates Detection using Color Reference Segmentation in Retinal Fundus Image. International Journal of Computer Applications 146(2):25-29, July 2016. BibTeX

@article{10.5120/ijca2016910692,
	author = {Diana Tri Susetianingtias and Sarifuddin Madenda and Rodiah},
	title = {An Approach to Exudates Detection using Color Reference Segmentation in Retinal Fundus Image},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2016},
	volume = {146},
	number = {2},
	month = {Jul},
	year = {2016},
	issn = {0975-8887},
	pages = {25-29},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume146/number2/25372-2016910692},
	doi = {10.5120/ijca2016910692},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The result of retinal images from fundus cameras are often provide unclear blood vessel of retinal images. As consequent, the ophthalmologists find it difficult to analyze the retinal images. Fundus images analyses require a longer time to achieve the test result especially for the patient with diabetic retinopathy. The research conducted in this paper introducing a space color reference approach to perform exudates segmentation. Exudates are one of the symptoms that cause diabetic retinopathy. The existence of exudates can be characterized by the appearance of fundus image in yellowish color with varying size and shape. The difficulties in exudates detection are due to the similar color intensity with optic disc (retinal blind spot), but with smaller size compare to optic disc. The study in this paper proposes color space approach where the object of interest area is used as exudates color references for retinal segmentation. The results of the experiments show that exudates detection based on color space reference are successfully segmented where the optic disc is not segmented as a part of exudates.

References

  1. Vaughan DG, Asbury T, Riordan Eva P. General Ophthalmology. Edisi 17. London: McGraw-Hill. (2007)
  2. Jack J. Kanski, Brad Bowling. Clinical Ophthalmology: A Systematic Approach 7th Edition. Butterworth Heinemann Elsevier. ISBN-13: 978-0702040931. (2011).
  3. B.Ramasubramanian and G.Mahendran. An Efficient Integrated Approach for the Detection of Exudates and Diabetic Maculopathy in Colour fundus Images. Advanced Computing: An International Journal ( ACIJ ), Vol.3, No.5. (2012)
  4. Joussen A.M.2007. Retinal Vascular Diseease. New York: Springer. p. 3-5, 66-70, 129-132, ,228-31, 309, 291-331
  5. Nidhal K. El Abbadi, Enas Hamood Al-Saadi. Automatic Detection of Exudates in Retinal Images. International Journal of Computer Science Issues Vol.10, Issue 2 No.1. ISSN (Print): 1694-0814 | ISSN (Online) : 1694-0784.(2013)
  6. Marwan D. Saleh, C.Eswaran and Ahmed Mueen. (2011). An Automated Blood Vessel Segmentation Algorithm Using Histogram Equalization and Automatic Threshold Selection. Journal of Digital Imaging.DOI: 10.1007/s10278-010=9302-9.
  7. Ratna Bhargavi and V. Rajesh. (2015). Detection And Feature Extraction Using Active Contour Model And Sift In Color Fundus Images. ARPN Journal of Engineering and Applied Sciences. VOL. 10, NO. 6.
  8. Sarifuddin Madenda. Pengolahan Citra & Video Digital. Teori, Aplikasi dan Pemrograman Menggunakan Matlab. Ed. Erlangga.ISBN. 978-602-298-598-3. (2015)
  9. Rodiah, Sarifuddin Madenda, Fitrianingsih. Three-Dimensional (3D) Reconstruction for Detectiong Shape and Volume of Lung Cancer Nodules. IPTEK Journal ITS. No.1. (2014).
  10. Priya, R., Aruna, P., Review of Automated Diagnosis Of Diabetic Retinopathy using The Support Vector Machine, International Journal of Applied Engineering Research, No. 4, Vol. 1, pp: 844-863. 2010
  11. Gonzalez R. C. and Woods E. E., Digital Image Processing. 3rd Edition. Prentice Hal;. (2007)

Keywords

Exudates, Fundus Image, Region of Interest, RGB Color Space, Segmentation