In this paper a contribution in the detection of diabetic symptoms using contrast enhancement of fundus images is proposed by synthesizing a hybrid neurofuzzy system via a sparsely-connected neural network. A fuzzy technique is firstly considered and a suitable coding of fuzzy rules is developed. A sparsely-connected neural network is then synthesized to provide enhanced contrast retinal images with bimodal histograms. Obtained contrast-enhanced images present pale areas that can more easily reveal suspect diabetic symptoms and enable accurate segmentations and measurements of the seriousness of diabetic symptoms. Experimental examples are reported.
Contrast Enhancement of Diabetic Retinal Images via a Hybrid Neurofuzzy System / Carnimeo, Leonarda; Giaquinto, A.. - In: WSEAS TRANSACTIONS ON SYSTEMS. - ISSN 1109-2777. - 5:7(2006), pp. 1595-1600.
Contrast Enhancement of Diabetic Retinal Images via a Hybrid Neurofuzzy System
CARNIMEO, Leonarda;
2006-01-01
Abstract
In this paper a contribution in the detection of diabetic symptoms using contrast enhancement of fundus images is proposed by synthesizing a hybrid neurofuzzy system via a sparsely-connected neural network. A fuzzy technique is firstly considered and a suitable coding of fuzzy rules is developed. A sparsely-connected neural network is then synthesized to provide enhanced contrast retinal images with bimodal histograms. Obtained contrast-enhanced images present pale areas that can more easily reveal suspect diabetic symptoms and enable accurate segmentations and measurements of the seriousness of diabetic symptoms. Experimental examples are reported.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
