Retinal image segmentation using texture, thresholding, and morphological operations

Retina blood vessel segmentation plays an important role in diagnosing the pathologies (diseases), which occur as swelling in parts of the vasculature, changing of width along blood vessels, and tortuosity that later on may cause blindness. In this paper, we have proposed a robust, combined method for blood tree segmentation on a 2D image. In our algorithms, the preprocessing takes place, such as image filtration and color contrast enhancement, and after that, the combined approach for image segmentation and classification are executed using texture, thresholding, and morphological operation. We tested our method on a number of fundus images with different views and intensities. Our method gives clearer and more accurate output for ophthalmologists, and automated retinal image diagnosis.