سال انتشار: ۱۳۸۴

محل انتشار: یازدهمین کنفرانس سالانه انجمن کامپیوتر ایران

تعداد صفحات: ۴

نویسنده(ها):

Alireza Osareh – Computer Science Department, Engineering Faculty, Chamran University of Ahwaz
Bita Shadgar –

چکیده:

Retinal exudates are a characteristic feature of many retinal diseases such as Diabetic Retinopathy. In this paper we address the development of a method to evaluate and quantitatively diagnose these random yellow patches in colour retinal images automatically. After an initial colour normalisation and contrast enhancement pre-processing step, colour retinal image pixels are classified to exudate and non-exudate classes. Gaussian quadratic, K nearest neighbour and Gaussian mixture model classifiers are examined within the pixel-level exudate recognition framework. A Gaussian mixture model-based classifier provided the best classification performance with 89.2% sensitivity and 81.0% predictivity in terms of pixel-level accuracy.