A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
International Journal of Computer Vision
Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation
International Journal of Computer Vision
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
A Framework for Image Segmentation Using Shape Models and Kernel Space Shape Priors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction
Journal of Scientific Computing
Combining shape, texture and intensity features for cell nuclei extraction in Pap smear images
Pattern Recognition Letters
TILT: transform invariant low-rank textures
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Using a geometric formulation of annular-like shape priors for constraining variational level-sets
Pattern Recognition Letters
A shape prior constraint for implicit active contours
Pattern Recognition Letters
IEEE Transactions on Image Processing
Minimization of Region-Scalable Fitting Energy for Image Segmentation
IEEE Transactions on Image Processing
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In this work, we propose a novel algorithm to extract geospatial objects with regular shape in remote sensing images, using shape-based global minimization active contour model (SGACM). Specially, we define a new energy function combining both image appearance information and object shape prior, and minimize it with an iterative global minimization method. In the proposed energy, not only image edge and color information are utilized, but also a new shadow region term is introduced to obtain more accurate extraction result; moreover, a new shape energy term in which we use kernel principle component analysis (KPCA) to model shapes is defined in our method, which provides good constraint on the extraction process and makes results more robust with respect to disturbances. In the energy numerical minimization process, Split Bregman method is used to get a global solution which overcomes the drawback of running into local minimum for the traditional level set method. Experiment results demonstrate more robustness and accuracy of our proposed method compared with others without shape constraint.