A diffusion approach to seeded image segmentation

Juyong Zhang, Jianmin Zheng, Jianfei Cai

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

60 Citations (Scopus)


Seeded image segmentation is a popular type of supervised image segmentation in computer vision and image processing. Previous methods of seeded image segmentation treat the image as a weighted graph and minimize an energy function on the graph to produce a segmentation. In this paper, we propose to conduct the seeded image segmentation according to the result of a heat diffusion process in which the seeded pixels are considered to be the heat sources and the heat diffuses on the image starting from the sources. After the diffusion reaches a stable state, the image is segmented based on the pixel temperatures. It is also shown that our proposed framework includes the RandomWalk algorithm for image segmentation as a special case which diffuses only along the two coordinate axes. To better control diffusion, we propose to incorporate the attributes (such as the geometric structure) of the image into the diffusion process, yielding an anisotropic diffusion method for image segmentation. The experiments show that the proposed anisotropic diffusion method usually produces better segmentation results. In particular, when the method is tested using the groundtruth dataset of Microsoft Research Cambridge (MSRC), an error rate of 4.42% can be achieved, which is lower than the reported error rates of other state-of-the-art algorithms.

Original languageEnglish
Title of host publication2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages8
ISBN (Print)9781424469840
Publication statusPublished - 2010
Externally publishedYes
EventIEEE Conference on Computer Vision and Pattern Recognition 2010 - San Francisco, United States of America
Duration: 13 Jun 201018 Jun 2010
https://ieeexplore.ieee.org/xpl/conhome/5521876/proceeding (Proceedings)


ConferenceIEEE Conference on Computer Vision and Pattern Recognition 2010
Abbreviated titleCVPR 2010
Country/TerritoryUnited States of America
CitySan Francisco
Internet address

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