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Retinal Image Segmentation Based on Texture Features

  • Shu Zhao
  • Weiyang ChenEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1075)

Abstract

Vessels segmentation is one of the key issues in the study of retinal image lesions. In this paper, a segmentation method of blood vessels using texture feature theory is introduced. This method is based on the texture features quantification and it is different from other blood vessel segmentation methods. We have quantified a large number of texture features that can be used in image processing. There are 41 kinds of texture features in all. The method presented in this paper is applied to retinal images in DRIVE and STARE databases. Through quantitative analysis of vascular texture features of retinal images, we found that several texture features, like gray variance, can easily identify the foreground and background of blood vessels, and thus can obtain better visual effect than the original image. It can provide more information for vessels segmentation and optic disc location.

Keywords

Retinal imaging Vessels segmentation Texture feature Gray variance 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyQilu University of Technology (Shandong Academy of Sciences)JinanChina

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