Blood vessels detection of diabetic retinopathy from retinal fundus image using morphological operations

الملخص EN

Early detection of eye diseases can forestall visual deficiency and vision loss.

There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension.

Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina.

Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases.

Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases.

Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision.

The aim of this reseaech is to utilized image processing techniques to detect blood vessels from the digital fundus images.

This research will present a methodology to separate retinal blood vessel network.

The suggested system in this research involves four stages, after image acquisition, the pre-processes of the image to preparing and improving the image quality is the first stage.

Morphological operations are used for the detection of blood vessels.

In this research, we use two morphological operations: erosion and dilation.

These two tasks have two sources of info, a binary image, and a structuring element object.

We utilize two morphological procedures ((boundary extraction and Top, Bottom Hat transform).

Before these operations, we will use applying a canny edge detector technique to obtain the edges of the retina image.

The technique is tried on shading retinal images acquired from STARE and DRIVE databases which are accessible on the web as well as the samples of retinal images were obtained from the digital camera from Ibn Al-Haytham specialist Hospital for Eye in Baghdad, Iraq.

The results obtained from these techniques showed the efficiency of these methods in the detection of blood vessels, especially when using morphological methods after the detection of edges