Journal of Computer Engineering & Information TechnologyISSN : 2324-9307

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Research Article, J Comput Eng Inf Technol Vol: 4 Issue: 3

A Robust Method for Finding Macular EDEMA Using GLCM Feature Extractor

Reshna T* and Shajy L
College of Engineering, Karunagappally, Kerala, India
Corresponding author : Reshna T, M. Tech
Computer Science (Image Processing), College of Engineering, Karunagappally, Kerala, India
Tel: 9447594171
E-mail: [email protected], [email protected]
Received: February 12, 2015 Accepted: October 01, 2015 Published: October 02, 2015
Citation: Reshna T, Shajy L (2015) A Robust Method for Finding Macular EDEMA Using GLCM Feature Extractor. J Comput Eng Inf Technol 4:3. doi:10.4172/2324-9307.1000134

Abstract

A Robust Method for Finding Macular EDEMA Using GLCM Feature Extractor

Diabetic Macular Edema (DME) is the most common cause of blindness. We can avoid the visual impairment by detecting DME in its early stage. To assess the effects of sight threatening disease on human vision, a two-stage methodology is proposed. That is for the detection and classification of DME severity from color fundus images, before significant visual loss. DME detection is carried out via a supervised learning approach using the normal fundus images. Global characteristics of the fundus images are captured through GLCM feature extraction technique for discriminate normal image from the diseased one. An algorithm based on rotational symmetry of macular region examines the severity of disease. The proposed method is an effective and clinically viable technique for detecting diabetic DME before visual loss.

Keywords: Retinal images; Diabetic Retinopathy; Support vector machine;Fundus image; Feature extraction; Classification

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