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A Structure Tensor Based Voronoi Decomposition Technique for Optic Cup Segmentation

Raj, PK and Harish Kumar, JR and Jois, S and Harsha, S and Sekhar Seelamantula, C (2019) A Structure Tensor Based Voronoi Decomposition Technique for Optic Cup Segmentation. In: 26th IEEE International Conference on Image Processing, ICIP 2019, 22- 25 September 2019, Taipei, pp. 829-833.

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Official URL: https://doi.org/10.1109/ICIP.2019.8804286


We present a technique for segmentation of optic cup based on the structural features found in blood vessels surrounding the optic cup region. The advantage of using such features is that they are robust to variations in the properties of the fundus image such as brightness, contrast, etc. The main features used in the technique are vessel bends (also called as landmark points or kinks), which are identified by applying the Harris corner detection algorithm on the optic disc region, followed by a Voronoi image decomposition. Pratt's circle fitting algorithm is employed on the extracted landmark points to segment the optic cup region. The proposed technique is validated on a total of 191 images taken from publicly available fundus image datasets, namely, Drishti-GS and MESSIDOR. Performance metrics such as sensitivity, specificity, accuracy, Jaccar�s index, and Dice coefficient are computed to be 85, 97, 96, 69.5, and 81, respectively, which indicates that the proposed technique for optic cup segmentation is competitive with the state-of-the-art methods. © 2019 IEEE.

Item Type: Conference Paper
Publication: Proceedings - International Conference on Image Processing, ICIP
Publisher: IEEE Computer Society
Additional Information: The copyright for this article belongs to IEEE Computer Society
Keywords: circle fit.; Harris corner detection; Optic cup segmentation; vessel bends; Voronoi decomposition
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 06 Jan 2023 07:23
Last Modified: 06 Jan 2023 07:23
URI: https://eprints.iisc.ac.in/id/eprint/78819

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