Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/2278
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dc.contributor.authorAnil Kumar, Neelapala-
dc.contributor.authorSatapathi, Gnane Swarnadh-
dc.contributor.authorAnuradha, Mosa Satya-
dc.date.accessioned2023-12-09T08:56:04Z-
dc.date.available2023-12-09T08:56:04Z-
dc.date.issued2022-
dc.identifier.citationpp. 1-5,en_US
dc.identifier.isbn9781665436472-
dc.identifier.urihttps://doi.org/10.1109/ICEEICT53079.2022.9768415-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2278-
dc.description.abstractIn this paper a novel technique on automated optical disk (OD) segmentation is proposed. The proposed OD algorithm depends on morphological based algorithm. This technique is assessed on openly accessible standard data sets DRIONS. The average accuracy rate of proposed segmented technique is 97.6% on DRIONS database. The proposed algorithm achieved Average Sensitivity, Average Specificity and Average Overlap of 93.1 %, 98.4% and 86.3% respectively on DRIONS data sets. Test results shows the algorithm is superior with comparable execution time over existing OD algorithms. Further, the algorithm has been implemented in System-on-chip (Zync-7000) kit. © 2022 IEEE.en_US
dc.language.isoenen_US
dc.publisher2022 1st International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2022en_US
dc.subjectDiabetic Retinopathyen_US
dc.subjectMorphological Operationen_US
dc.subjectOptic disken_US
dc.subjectRetinal imageen_US
dc.titleSystem-on-Chip Based Automated Optic Disk Segmentation In Retinal Imagesen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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