Abstract
This paper presents a new and fast multiphase image segmentation model for color images. We propose our model by incorporating the globally convex image segmentation method and the split Bregman method into the piecewise constant multiphase Vese‐Chan model for color images. We have applied our model to many synthetic and real color images. Numerical results show that our model can segment color images with multiple regions and represent boundaries with complex topologies, including triple junctions. Comparison with the Vese‐Chan model demonstrates the efficiency of our model. Besides, our model does not require a priori denoising step and is robust with respect to noise.
Highlights
Image segmentation [1,2,3,4,5,6,7,8] is an important technique for detecting objects and analyzing images in computer vision and image processing
In our previous work, we have proposed an improved active contour model for multiphase image segmentation based on the piecewise constant multiphase Vese-Chan model 3, the globally convex image segmentation method and the split Bregman method [15,16,17]
The advantage of using binary step functions as the initial level set functions is that new contours can emerge and the curve evolution is significantly faster than the evolution from initial functions as signed distance maps
Summary
Image segmentation [1,2,3,4,5,6,7,8] is an important technique for detecting objects and analyzing images in computer vision and image processing. To deal with images with multiple regions, Vese and Chan extended their original two-phase Chan-Vese model [1, 2] to a multiphase model by using a multiphase level set formulation in 3. Zhao et al , Samson et al , and Paragios and Deriche have already proposed several multiphase image segmentation models to segment images with multiple regions before the multiphase Vese-Chan model These models have the natural problems of vacuum and overlap. We propose a fast multiphase image segmentation model in a variational level set formulation for color images. Numerical results show that our model has the advantages of the original Vese-Chan model 3 for multiphase image segmentation, but our model is much more efficient.
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