2017 11th International Conference on Information &Amp; Communication Technology and System (ICTS) 2017
DOI: 10.1109/icts.2017.8265642
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Exudate detection in retinal fundus images using combination of mathematical morphology and Renyi entropy thresholding

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Cited by 14 publications
(6 citation statements)
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“…Due to pixel-based criteria, other bright yellowish pixels such as cottonwool spots have been miss segmented at the same time. For morphological-based segmentation, to address the issue raised by D. U. N. Qomariah et al [11] extracted EXs in two classes: normal and abnormal. The author made the pre-processing stage with contrast enhancement.…”
Section: Previous Related Workmentioning
confidence: 99%
“…Due to pixel-based criteria, other bright yellowish pixels such as cottonwool spots have been miss segmented at the same time. For morphological-based segmentation, to address the issue raised by D. U. N. Qomariah et al [11] extracted EXs in two classes: normal and abnormal. The author made the pre-processing stage with contrast enhancement.…”
Section: Previous Related Workmentioning
confidence: 99%
“…The mathematical morphological technique is one of the most primitive segmentation techniques which utilize the mathematical operators having various structural elements. A combined methodology of mathematical-morphology with regional-minima and dilation approach which is proposed by Qomariah et al 6 Kaur et al 7 used a flexible region-developing technique to detect the hard exudates by choosing a fixed threshold. The region growing-based technique for exudates segmentation has achieved 97.9% sensitivity and 99.4% specificity.…”
Section: Retinal Lesion Segmentationmentioning
confidence: 99%
“…According to authors of [13], L* layer of L*u*v* colour model can help in easy exudate extraction. The extracted L* colour model is made to undergo top hat transform.…”
Section: Fpga and Matlab Based Solution For Retinal Exudate Detectionmentioning
confidence: 99%