Variational level set image segmentation method based on Landmark simplex constraint
A technology of image segmentation and level set, which is applied in image analysis, image data processing, instruments, etc., can solve the problem that prior features cannot be integrated, and achieve high segmentation performance and good segmentation results
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[0036] A variational level set image segmentation method based on Landmark simplex constraints involved in this embodiment is realized through the following technical solutions:
[0037] S1. Determination of Landmark point features: Scale Invariant Feature Transform (SIFT) points are not sensitive to image noise, so this patent uses SIFT simple features to explicitly extract Landmark point features based on the non-maximum suppression framework. It mainly includes (1) using difference of Gaussian (DOG) function to establish Gaussian scale space; (2) scale space extremum detection and key point location.
[0038] S2. Variational level set expression of Landmark point features: based on the VLSM framework, assuming LM={lm 1 ,lm 2 ,...,lm l} is the Landmark point feature, if x∈LM, then the mask function η(x)=1, otherwise η(x)=0, the level set function φ will constrain φ(x)η(x)=0 along the Landmark point Evolution; In addition, the present embodiment also adopts simplex project...
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