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dc.contributor.authorHaniza, Yazid
dc.contributor.authorHamzah, Arof, Dr.
dc.contributor.authorHazlita, Mohd Isa, Dr.
dc.date.accessioned2013-05-15T06:46:49Z
dc.date.available2013-05-15T06:46:49Z
dc.date.issued2012-07
dc.identifier.citationMeasurement, vol. 45 (6), 2012, pages 1599–1608en_US
dc.identifier.issn0263-2241
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0263224112000954
dc.identifier.urihttp://dx.doi.org/10.1016/j.measurement.2012.02.016
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/25488
dc.descriptionLink to publisher's homepage a http://www.journals.elsevier.com/measurement/en_US
dc.description.abstractThis paper presents a new approach to detect exudates and optic disc from color fundus images based on inverse surface thresholding. The strategy involves the applications of fuzzy c-means clustering, edge detection, otsu thresholding and inverse surface thresholding. The main advantage of the proposed approach is that it does not depend on manually selected parameters that are normally chosen to suit the tested databases. When applied to two sets of databases the proposed method outperforms methods based on watershed segmentation and morphological reconstruction. The proposed method obtained 98.2 and 90.4 in terms of sensitivity for Standard Diabetic Retinopathy Database – Calibration Level 1 (DIARETDB1) and a local dataset provided by National University Hospital of Malaysia (NUHM), respectively.en_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.subjectThresholdingen_US
dc.subjectImage segmentationen_US
dc.subjectMedical imagesen_US
dc.subjectDiabetic retinopathyen_US
dc.subjectBiomedical applicationsen_US
dc.subjectInverse surface thresholdingen_US
dc.titleExudates segmentation using inverse surface adaptive thresholdingen_US
dc.typeArticleen_US


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