ABSTRACT -- Aim-- To recognise automatically the main components of the fundus on digital colour images. Methods--The main features of a fundus retinal image were defined as the optic disc and blood vessels. We describe methods for their automatic recognition and location. 112 retinal images were pre-processed via adaptive, local, contrast enhancement. The optic discs were located by identifying the area with the highest variation in intensity of adjacent pixels. Blood vessels were identified by means of a multilayer perceptron neural net, for which the inputs were derived from a principal component analysis of the image and edge detection of the intensity. The main components of the image were identified by an experienced ophthalmologist for comparison with computerised methods. Results-- The sensitivity and specificity of the recognition of each retinal main component was as follows: 99.1% and 99.1% for the optic disc; 83.3% and 91.0% for blood vessels. Conclusions-- In this study the optic disc and blood vessels were accurately detected. The identification of the normal components of the retinal image will aid the future detection of diseases of these regions. In diabetic retinopathy, for example, an image could be analysed for retinopathy with reference to sight threatening complications. It is also apply with the technique Image registration to register Colour retinal Image with the fluorescein image. This assists clinician to locate the position of abnormality areas easier.

KEYWORDS -- Image Analysis, Image Recognition, Neural Network, Diabetic Diagnosis, Retinopathy