
Proceedings Paper
A rapid gradient segmentation method for edge recognition of biomedical imageFormat | Member Price | Non-Member Price |
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Paper Abstract
Image edge recognition is a crucial aspect of biomedical image processing. In this paper, a rapid gradient segmentation
method based on the depth-first traverse of images is presented. This method defines the data structure for the pixel
firstly, estimate and catch gradient from four pixels around the arbitrary point coming from an arbitrary pixel of image. If
the pixel satisfies the feature of edge, the edge perpendicular to the directions of gradient is processed by depth-first
traverse, the pixels are marked at the same time. It will withdraw when no pixels satisfy the feature in the directions, then
depth-first traverse from the next direction with gradient, mark the pixel as corner, and traverse the image completely.
The segmentation method has been applied to edge recognition of color biomedical image and other images. The
experimental results showed that edges and corners of biomedical image can be segmented obviously, and be easy to
identify.
Paper Details
Date Published: 1 May 2007
PDF: 4 pages
Proc. SPIE 6534, Fifth International Conference on Photonics and Imaging in Biology and Medicine, 65342W (1 May 2007); doi: 10.1117/12.741438
Published in SPIE Proceedings Vol. 6534:
Fifth International Conference on Photonics and Imaging in Biology and Medicine
Qingming Luo; Lihong V. Wang; Valery V. Tuchin; Min Gu, Editor(s)
PDF: 4 pages
Proc. SPIE 6534, Fifth International Conference on Photonics and Imaging in Biology and Medicine, 65342W (1 May 2007); doi: 10.1117/12.741438
Show Author Affiliations
Guan-nan Chen, Huazhong Univ. of Science and Technology (China)
Key Lab. of OptoElectronic Science and Technology for Medicine, Fujian Normal Univ. (China)
Zhong-jian Teng, Key Lab. of OptoElectronic Science and Technology for Medicine, Fujian Normal Univ. (China)
Key Lab. of OptoElectronic Science and Technology for Medicine, Fujian Normal Univ. (China)
Zhong-jian Teng, Key Lab. of OptoElectronic Science and Technology for Medicine, Fujian Normal Univ. (China)
Kun-tao Yang, Huazhong Univ. of Science and Technology (China)
Rong Chen, Key Lab. of OptoElectronic Science and Technology for Medicine, Fujian Normal Univ. (China)
Rong Chen, Key Lab. of OptoElectronic Science and Technology for Medicine, Fujian Normal Univ. (China)
Published in SPIE Proceedings Vol. 6534:
Fifth International Conference on Photonics and Imaging in Biology and Medicine
Qingming Luo; Lihong V. Wang; Valery V. Tuchin; Min Gu, Editor(s)
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