@article{Farzin_Moghaddam_Moin_2024, title={New Method for Blood Vessels Segmentation in Retinal Images}, volume={1}, url={https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/new-method-for-blood-vessels-segmentation-in-retinal-images/}, DOI={10.1234/mjee.v1i1.47}, abstractNote={Retinal image analysis has many applications in various fields such as biometrics or medical diagnosis. Blood vessel segmentation is the first and important stage in these analyses. This paper presents an efficient method for automatic segmentation of blood vessels in retinal images. In the first stage, the proposed algorithm uses a template matching technique for reducing the effect of optical disk in the image. Then, it uses a new local processing operation based on the statistical properties of the image in order to enhance the vessel/background contrast. Next morphological operations are used for filling the vessel spaces caused by the previous stages. Finally, a binary image containing blood vessels is resulted by histogram thresholding of the contrast enhanced image. Evaluation of the results obtained by the new segmentation algorithm demonstrated its superior sensitivity and comparable accuracy with respect to the results of the previous works.}, number={1}, journal={Majlesi Journal of Electrical Engineering}, publisher={OICC Press}, author={Farzin, Hadi and Moghaddam, Hamid Abrishami and Moin, Mohammad-Shahram}, year={2024}, month={Feb.}, keywords={Gain Tuning, Retinal images, Retinal Identification, Blood Vessels Segmentation} }