Detection and Classification of Cataract  using Fuzzy Inference System

Sambhoo, Kalyani

dc.contributor.author	Sambhoo, Kalyani
dc.date.accessioned	2020-02-04T06:08:28Z
dc.date.available	2020-02-04T06:08:28Z
dc.date.issued	2009
dc.identifier.citation	YCMOU, Nashik	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/96
dc.description	In this dissertation, an effort has been made to automate the cataract detection, classification and grading method. Algorithms have been developed which detect the presence of cataract. Currently, the detector enhances the image quality, and works on cropped images which depict only the region of interest i.e. the pupil in an eye image using MATLAB functions and then computes the pixel colour which are crisp (non fuzzy) numbers limited within a specific range are sent as input to a Fuzzy Inference System. Rules are designed which execute using fuzzy reasoning of membership functions. The input to an if-then rule is the current value for the input variable and the output is an entire fuzzy set . This fuzzy set is later defuzzified to obtain a crisp result assigning one value to the output which is a crisp result i.e. non-cataract or cataract and is further classified into its types. With little modification, proposed model can be used as a tool for semi-automated cataract detection and classification.	en_US
dc.language.iso	en	en_US
dc.subject	COMPUTER SCIENCE	en_US
dc.subject	FUZZY LOGIC	en_US
dc.subject	FUZZY INFERENCE SYSTEM	en_US
dc.subject	DETECTION OF CATARACT USING FUZZY INFERENCE SYSTEM	en_US
dc.subject	IMPACT OF COMPUTER ON MEDICAL SCIENCE	en_US
dc.subject	CATARACTION DETECTION AND FUZZY LOGIC	en_US
dc.subject	CATARACT DETECTION AND COMPUTER SCIENCE	en_US
dc.subject	CATARACT DETECTION ALGORITHM	en_US
dc.subject	FUZZY LOGIC OPERATORS	en_US
dc.subject	OPTHALMOLOGY	en_US
dc.title	Detection and Classification of Cataract using Fuzzy Inference System	en_US
dc.type	M.Phil Dissertation	en_US