Detection of bifurcations and cross-over points from retinal vasculature map using modified window feature-point detection approach

Abstract

Identification of feature points such as bifurcation points and cross-over points in retinal fundus images is useful for predicting the various cardiovascular diseases. In this paper, a new approach called the Modified Window Feature-point Detection (MWFD) is proposed to identify the vascular feature points in the fundus image. The MWFD technique makes use of two different windows 3�3 and 5�5 with alternative vessel pixel property for the detection of all feature points. This paper also resolves the problem of conversion of one cross-over point into two bifurcation points generated due to skeletonisation. The simulation is performed on the DRIVE database using MATLAB software. Simulation results show quantitative improvements in detection of feature points from retinal fundus image by increasing the number of true positives and reducing false positives and false negatives. These results provide an efficient and reliable technique for analysis of various retinal structures.