Detection of Retinal Blood Vessels Based on Morphological Analysis with Multiscale Structure Elements and SVM Classification

作者：Kim Pil Un^*; Lee Yunjung; Woo Sanghyo; Won Chulho; Cho Jin Ho; Kim Myoung Nam

来源：IEICE Transactions on Information and Systems, 2011, E94D(7): 1519-1522.

DOI：10.1587/transinf.E94.D.1519

• retina vessel
• vessel detection
• fundus image
• support vector machine
• morphological feature

Since retina blood vessels (RBV) are a major factor in ophthalmological diagnosis, it is essential to detect RBV from a fundus image. In this letter, we proposed the detection method of RBV using a morphological analysis and support vector machine classification. The proposed RBV detection method consists of three strategies: pre-processing, features extraction and classification. In pre-processing, noises were reduced and RBV were enhanced by anisotropic diffusion filtering and illumination equalization. Features were extracted by using the image intensity and morphology of RBV. And a support vector machine (SVM) classification algorithm was used to detect RBV. The proposed RBV detection method was simulated and validated by using the DRIVE database. The averages of accuracy and TPR are 0.94 and 0.78, respectively. Moreover, by comparison, we confirmed that the proposed RBV detection method detected RBV better than the,recent RBV detections methods.

• 出版日期2011-7