Erwin, Erwin (2022) Retinal Blood Vessel Extraction Using a New Enhancement Technique of Modi¯ed Convolution Filters and Sauvola Thresholding. International Journal of Image and Graphics, 2022 (235000). pp. 1-23. ISSN 1793-6756
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Abstract
The retinal blood vessels on humans are major components with different shapes and sizes. The extraction of the blood vessels in the retinal is an important step to identify the type or nature of the pattern of the diseases in the retinal. Furthermore, the retinal blood vessel was also used for diagnosis, detection, and classification. The most recent solution in this topic is to enable retinal image improvement or enhancement by convolution filter and Sauvola threshold. In image enhancement, gamma correction is applied before filtering the retinal fundus. After that, the image should be transformed to a gray channel to enhance pictorial clarity using contrast limited histogram equalization. For filter, this paper combines two convolution filters, namely sharpen and smooth filters. The Sauvola threshold, the morphology, and the medium filter are applied to extract blood vessels from the retinal image. This paper use DRIVE and STARE datasets. The accuracies of the proposed method are 95.37% for DRIVE with a runtime of 1.77 seconds and 95.17 % for STARE with 2.05 seconds of runtime. Based on the result, it concludes that the proposed method is good enough to achieve average calculation parameters of a low time quality, quick and significant.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. |
| Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
| Depositing User: | Dr Erwin Erwin |
| Date Deposited: | 25 Feb 2022 05:48 |
| Last Modified: | 25 Feb 2022 05:48 |
| URI: | http://repository.unsri.ac.id/id/eprint/65160 |
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- Retinal Blood Vessel Extraction Using a New Enhancement Technique of Modi¯ed Convolution Filters and Sauvola Thresholding. (deposited 25 Feb 2022 05:48) [Currently Displayed]
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