A Novel Method for Identifying Retinal Blood Vessels using Fractional Fuzzy Local Binary Patterns

Detection of blood vessels in retinal is a primary step for diagnose hypertension and glaucoma. Numerous techniques have been developed for detection of retinal blood vessels but lack of robustness. In this paper, a new method is presented to improve the accuracy of finding retinal blood vessels and to remove the unwanted hair line by fractional fuzzy local binary pattern (FFLBP). In FFLBP several membership functions is applied for each pixels and the membership function having maximum entropy is opted as membership function for the corresponding pixel and new weightage matrix have been introduced for find local binary pattern(LPB) code. After applying FFLBP, it gives improved results along with the removal of hair lines. The results of the presented method are compared with existing edge detection methods. Quantitative measures show that the presented work gives finer performance.