Identification of exudates using fuzzy mathematical morphology

dc.contributor.authorWisaeng, Kittipol
dc.contributor.authorHiransakolwong, Nualsawat
dc.contributor.authorPothiruk, Ekkarat
dc.date.accessioned2026-08-06T10:08:08Z
dc.date.available2026-08-06T10:08:08Z
dc.date.issued2014-01-01
dc.description.abstractDiabetic Retinopathy is the damage to the retina caused by complication and the most common cause of blindness in Thailand. Retinal image is essential for expert ophthalmologists to diagnose diseases. Several of method can achieve good performance on retinal feature are clearly visible. Unfortunately, the color retinal image in Thailand are low-resolution images. The existing method cannot identified lowresolution image. Therefore, this study is part of a larger effort to develop a new method for identification of exudates in low-resolution retinal image. In this study a fuzzy mathematical morphology based on fuzzy logical operator and mathematical morphology method is presented. The color retinal image are segmented by using fuzzy logical operator following key preprocessing step, i.e., color normalization, contrast enhancement, noise removal and color space selection. Afterward, a segmentation using mathematical morphology method was applied in this step. This enables its difference in our methods compared to other approach and the methods can achieve good performance even on lowresolution retinal images. Respect to the experimental results, the results obtained with fuzzy mathematical morphology better than the ones obtained with the fuzzy logical operator only method.
dc.identifier.citationJournal of Computer Science, 10(5), 852-860, 2014
dc.identifier.doi10.3844/jcssp.2014.852.860
dc.identifier.issn15493636
dc.identifier.other2-s2.0-84987615941
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/5288
dc.sourceJournal of Computer Science
dc.subjectDiabetic retinopathy
dc.subjectExpert ophthalmologists
dc.subjectExudates
dc.subjectFuzzy mathematical morphology
dc.subjectRetinal image
dc.titleIdentification of exudates using fuzzy mathematical morphology
dc.typeArticle

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