Study of Segmentation Algorithm Based on Corneal Endothelial Cell Images

Ru Min Yang; Shuai Wang; Cheng Bo Yu; Jing Jing Hu; Yi Ju Yang

doi:10.4028/www.scientific.net/AMR.1030-1032.2377

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1030-1032Study of Segmentation Algorithm Based on Corneal...

Study of Segmentation Algorithm Based on Corneal Endothelial Cell Images

Abstract:

In this paper, we study an an algorithm for accurately extracting the outline of Corneal Endothelial Cell images according to the structure and feature of the corneal endothelial cells. Firstly, we reduce the influence of uneven exposure to segmentation effect using histogram equalization. Secondly, reduce the image noise by Gaussian filtering. At last, research the classical algorithm of image segmentation through the contrast experiment and then select a simple and effective local NiBlack dynamic threshold algorithm. The experimental result shows that this processing method is not only simple, but also can segment the corneal endothelial cell images clearly, and provides a good foundation of data for accurate identification of the following images.

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Periodical:

Advanced Materials Research (Volumes 1030-1032)

Pages:

2377-2381

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1030-1032.2377

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Online since:

September 2014

Authors:

Ru Min Yang*, Shuai Wang, Cheng Bo Yu, Jing Jing Hu, Yi Ju Yang

Keywords:

Corneal Endothelial Cells, Image Segmentation, NiBlack Algorithm

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References

[1] Zhao Lichu, Shi Pengfei. The contour extraction of corneal endothelial celll[J]. Journal of infrared and millimeter waves, 2002. 2, 1(19).

Google Scholar

[2] Yang Hongwei, Zhang Yun. Feature extraction of blood cells based on image processing [J]. Bioinformatics, 2005 (2).

Google Scholar

[3] Zhao Lin, Sun Hongchen. Affects of various factors on corneal endothelial cells morphology [J] International Journal of Ophthalmology" the third people, s hospital of ophthalmology, Dalian City, Liaoning Province, China. 2008. 7, 8 (7).

Google Scholar

[4] Wang Jianfa, WangXueqiao. The corneal endothelial cell image processing method, 200710003 661. X, [P] 2007. 1.

Google Scholar

[5] Khan, Mohammad A. U, Khan, M. Khalid, Khan, M. Aurangzeb, Ibrahim, M. Talal. Endothelial cell image enhancement using non-subsampled image pyramid Information Technology Journal, v 6, n 7, pp.1057-1062, October 1, (2007).

DOI: 10.3923/itj.2007.1057.1062

Google Scholar

[6] Yu Chengbo, Qin Huafeng. The research of finger vein image feature extraction algorithm [J]. Computer Engineering and Applications, 2008, 44(24).

Google Scholar

[7] Yu Chengbo. Finger vein recognition technology [M] Beijing: Tsinghua University press, (2008).

Google Scholar