Soft Computing

, Volume 22, Issue 5, pp 1501–1509 | Cite as

Automatic vessel segmentation on fundus images using vessel filtering and fuzzy entropy

  • Huiqian Wang
  • Yuhao Jiang
  • Xiaoming JiangEmail author
  • Jun Wu
  • Xiaomin Yang


Vessel segmentation is a critical and challenging task for fundus image processing, which is precursor and essential first step to further vessel measurement and diagnosis. This paper proposes a novel hybrid automatic vessel segmentation method for the delineation of vessels on fundus images. The method consists of two main steps including Hessian-based vessel filtering and vessel segmentation. In vessel filtering, multi-scale linear filtering based on Hessian matrix is adapted to enhance vessels in the image. After vessel filtering, a novel two-dimensional histogram of filtering image is generated. Then, the thresholds are determined by the fuzzy entropic concepts. We demonstrate the effectiveness of the proposed method on real fundus images from DRIVE database. Quantification analysis is applied through three metrics with respect to manual delineated ground truth from one specialist. Compared to three other methods, the proposed method yields more complete and accurate results.


Vessel segmentation Fundus image Hessian matrix Vessel filtering Fuzzy entropic thresholding 



This work is supported by the National Science Foundation of China (Grant Nos. 61471075, 61671091), National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2014BAI11B10), Chongqing Integrated Demonstration Project (CSTC2013jcsf10029), Wenfeng Innovation Foundation of CQUPT, University Innovation Team Construction Plan Funding Project of Chongqing (Smart Medical System and Key Techniques, CXTDG201602009), Chongqing Key Laboratory Improvement Plan (Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology, cstc2014pt-sy40001), Chongqing Research Program of Basic Research and Frontier Technology (cstc2017jcyjBX0057, cstc2017jcyjAX0328), Science and Technology research project of Chongqing Education Commission (KJ1704073), the Scientific Research Foundation of CQUPT(A2016-73), Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD) Fund, and Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology(CICAEET) Fund.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Huiqian Wang
    • 1
  • Yuhao Jiang
    • 1
  • Xiaoming Jiang
    • 1
    Email author
  • Jun Wu
    • 2
  • Xiaomin Yang
    • 3
  1. 1.Chongqing University of Posts and TelecommunicationsChongqingChina
  2. 2.Kaize CompanyChongqingChina
  3. 3.Sichuan UniversityChengduChina

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