Retinal Blood Vessel Segmentation Using Otsu Thresholding With Principal Component Analysis

Fundus images are consistently used for the analysis of numerous pathological syndromes. This paper presents a three step thresholding based method to extract the blood vessels from the retinal images. In the first step a unique combination of principal component analysis (PCA) and contrast limited adaptive histogram equalization (CLAHE) is used to enhance the retinal images. In the second step the blood vessels are extracted with the help of global Otsu thresholding method. Finally in the last step morphological cleaning is applied to remove unwanted frills. The proposed method enables implementation to be easier and takes less computational time. The two publicly available DRIVE and STARE databases are taken for evaluation of the performance of the presented method. It achieves an average accuracy, sensitivity and specificity about 0.956, 0.723 and 0.984 for DRIVE database while 0.954, 0.737 and 0.982 for STARE database respectively.