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Automatic localization of optic disk based on texture orientation voting

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Abstract

Automatic localization of optic disk is a challenging problem due to the interference of multiple factors. In this paper, we aim at the study of the optic disk localization method and propose a simple and efficient method based on texture orientation voting. This method uses multi-directional Gabor filters to detect the texture orientations of fundus images. Before orientation voting, texture orientation extraction and orientation confidence computation are conducted. Only the texture orientations with high confidence could participate in orientation voting. If the texture orientation of a voter pixel points at a receiver pixel, the receiver will get a vote from the voter, which is weighted according to the positional relationship of the voter and the receiver. The pixel with the maximum vote over the image will be taken as the optic disk location. In a variety of difficult environments, an average OD detection accuracy of 96.8% is obtained and the experimental results verify the efficiency and robustness of our proposed method.

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Acknowledgements

This work was supported by the National Key Research and Development Program of China for high performance computing under Grant 2016YFB0201503, the 13th Five-Year Plan of the Science and Technology Research of the Education Department of Jilin Province under Grant 2016433, National Natural Science Foundation of China under Grant 60905022, and Ph.D. Program Foundation of the Ministry of Education of China under Grant 20130061110054.

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  1. Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, Jilin, People’s Republic of China

    Xiaoxin Guo, Qun Li & Chao Sun

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  1. Xiaoxin Guo
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  2. Qun Li
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  3. Chao Sun
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Correspondence to Xiaoxin Guo.

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Guo, X., Li, Q. & Sun, C. Automatic localization of optic disk based on texture orientation voting. SIViP 11, 1115–1122 (2017). https://doi.org/10.1007/s11760-017-1065-z

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