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Essential image processing and analysis tasks, such as image segmentation, simplification and denoising, can be conducted in a unified way by minimizing the Mumford-Shah (MS) functional. Although seductive, this minimization is in practice difficult because it requires to jointly define a sharp set of contours and a smooth version of the initial image. For this reason, various relaxations of the original...
In this research, an object-oriented image classification framework was developed which incorporates nonlinear scale-space filtering into the multi-scale segmentation and classification procedures. Morphological levelings, which possess a number of desired spatial and spectral properties, were associated with anisotropically diffused markers towards the construction of nonlinear scale spaces. Image...
Pose editing, changing the poses of three-dimensional (3D) mesh model, frequently results in de-synchronization effect which most 3D watermarking methods are sensitive to and normally regard it as an attack. A novel pose-invariant blind watermarking algorithm for 3D triangular mesh model is proposed in this paper to resist the pose changing attack. In this algorithm, the geodesic distance of each...
In this paper, we simplify the model of local binary model and propose an improved region-based active contour model for medical image segmentation. Our model combines the advantages of the simplification of local binary fitting model by taking the local intensity information and the speed function using the minimal variance term, which enable the model to cope with intensity inhomogeneity. We define...
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