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9 June 2015 Level set method for image segmentation based on moment competition
Hai Min, Xiao-Feng Wang, De-Shuang Huang, Jing Jin, Hong-Zhi Wang, Hai Li
Author Affiliations +
Abstract
We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.
© 2015 SPIE and IS&T 1017-9909/2015/$25.00 © 2015 SPIE and IS&T
Hai Min, Xiao-Feng Wang, De-Shuang Huang, Jing Jin, Hong-Zhi Wang, and Hai Li "Level set method for image segmentation based on moment competition," Journal of Electronic Imaging 24(3), 033020 (9 June 2015). https://doi.org/10.1117/1.JEI.24.3.033020
Published: 9 June 2015
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

Distributed interactive simulations

Performance modeling

Diffusion

Image filtering

Image processing algorithms and systems

Roads

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