Conference or Workshop Item #8311

(2017) Circlet based framework for optic disk detection. In: 24th IEEE International Conference on Image Processing, ICIP 2017, 17 September 2017 through 20 September 2017, China National Convention Center (CNCC)Beijing; China.

Full text not available from this repository.

Abstract

Optic Disc (OD) detection in retinal fundus images is a crucial stage for the automation of a screening system in diabetic ophthalmology. Most researches for automatic localization of OD benefit the regions of vessels. In this paper, we present a fast and novel method based on the Circlet Transform to detect OD in digital retinal fundus images that doesn't utilize the location of the vessels. First, each R, G and B band is enhanced using CLAHE method. Then, the enhanced image in RGB color space is converted to L-a-b one. Next, the Circlet transform is applied to the L- band, and finally, the Circlet transform coefficients are analyzed to find the location of the OD. The proposed algorithm is implemented on DRIVE dataset and the experimental results show a very well OD localization. The correct rate of the proposed method is 95 even though it doesn't utilize the vessels' structure. © 2017 IEEE.

Item Type: Conference or Workshop Item (Paper)
Keywords: Circlet coefficients Circlet Transform Digital Retinal Fundus Images Image Enhancement Optic Disk Detection Ophthalmology Optical data processing Automatic localization Optic disc Optic disk detections Retinal fundus images RGB color space Screening system Transform coefficients
Divisions: Medical Image and Signal Processing Research Center
School of Advanced Technologies in Medicine > Department of Bioelectrics and Biomedical Engineering
Page Range: pp. 3330-3334
Journal Index: Scopus
Volume: 2017-S
Publisher: IEEE Computer Society
Identification Number: https://doi.org/10.1109/ICIP.2017.8296899
ISBN: 15224880 (ISSN); 9781509021758 (ISBN)
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/8311

Actions (login required)

View Item View Item