Optic disc (OD) localization plays an important role in the automatic screening of ocular fundus diseases. However, it is still a challenge at present to balance the accuracy and efficiency of the OD localization for various of retinal fundus images. In this paper, we propose a new framework to integrate two classes methods based on image intensity and vascular information to obtain the OD location. The classification algorithm within the framework is based on a verification model. Firstly, an OD candidate region is obtained by image intensity. Secondly, the candidate region is validated by verification model. If the verification is passed, the corresponding position of the region is determined as the OD center. Otherwise, the OD is located by the parabola fitting of the main blood vessels and the relocation. The proposed method was evaluated on four public databases STARE, DRIVE, DIARETDB0 and DIARETDB1, and the accuracy rate was 96.3%, 100%, 100% and 100%, respectively. The running time is 0.05 s, 0.03 s, 0.13 s and 0.12 s per image through the validation in each database, while the time spent on images failed in verification is about 0.49 s, 0.38 s, 2.21 s and 2.15 s, individually. (C) 2017 Elsevier Ltd. All rights reserved.
[Wang, Haodong] Department of Electrical Engineering and Computer Science, Cleveland State University, OH, 44115, United States;[Wang, Jianxin; Wang, Haodong; Zhang, Shigeng] School of Information Science and Engineering, Central South University, Changsha, China;[Xiao, Yalong] College of Literature and Journalism, Central South University, Changsha, China;[Cao, Jiannong] Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
[Wang, Jianxin] Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China.
Indoor localization;Fingerprinting method;Channel state information;KL divergence