A Hybrid Genetic Algorithm based Fuzzy Approach for Abnormal Retinal Image Classification

Autor:	D. Jude Hemanth, J. Anitha, C. Kezi Selva Vijila
Rok vydání:	2010
Předmět:	Computer science business.industry Pattern recognition Fuzzy logic Retinal image Human-Computer Interaction Fuzzy classifier ComputingMethodologies_PATTERNRECOGNITION Artificial Intelligence Artificial intelligence business Feature set Classifier (UML) Software
Zdroj:	International Journal of Cognitive Informatics and Natural Intelligence. 4:29-43
ISSN:	1557-3966 1557-3958
DOI:	10.4018/jcini.2010070103
Popis:	Fuzzy approaches are one of the widely used artificial intelligence techniques in the field of ophthalmology. These techniques are used for classifying the abnormal retinal images into different categories that assist in treatment planning. The main characteristic feature that makes the fuzzy techniques highly popular is their accuracy. But, the accuracy of these fuzzy logic techniques depends on the expertise knowledge, which indirectly relies on the input samples. Insignificant input samples may reduce the accuracy that further reduces the efficiency of the fuzzy technique. In this work, the application of Genetic Algorithm (GA) for optimizing the input samples is explored in the context of abnormal retinal image classification. Abnormal retinal images from four different classes are used in this work and a comprehensive feature set is extracted from these images as classification is performed with the fuzzy classifier and also with the GA optimized fuzzy classifier. Experimental results suggest highly accurate results for the GA based classifier than the conventional fuzzy classifier.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::94bd7a202901dae1af3d8bded7ab77cd https://doi.org/10.4018/jcini.2010070103 Zobrazit plný text záznamu