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Frequency-tuned active contour model
Neurocomputing, 2018Abstract Active contour model (ACM) is able to obtain sub-pixel precision segmentation and has been widely employed in biomedical image analysis and video segmentation. Existing region-based ACMs (RACM) without enough prior constraints, however, easily fail when segmenting low quality images, e.g.
Qing Guo 0005 +5 more
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Double Contour Active Shape Models
Procedings of the British Machine Vision Conference 2005, 2005Statistical shape models are often learned from examples based on landmark correspondences between annotated examples. A method is proposed for learning such models from contours with inconsistent bifurcations and loops. It is evaluated on the task of segmenting tibial contours in knee radiographs. Results are presented using various features, distance
Matthias Seise +3 more
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Face contour tracking in video using active contour model
2004 International Conference on Image Processing, 2004. ICIP '04., 2005Face contour represents important information used for human face analysis in image and video. Here, we propose an improvement to the conventional active contour model, called Snake, to track complex face contour. We propose using gradient angular difference (GAD) to constrain the Snake contour to the specific face region.
Xiong Bing +2 more
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An Active Contour Model for Selective Segmentation
International Conference on Computer Graphics, Imaging and Visualization (CGIV'05), 2005In this paper, we develop a new active contour model for image selective segmentation. The model adopts cascade anisotropic diffusion preprocessing and a selective term in level set function. Cascade anisotropic diffusion filtering is powerful and flexible to enhance image for various segmentation tasks.
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Image Contour Extraction Based on CNN and Active Contour Model
2009 Fifth International Conference on Natural Computation, 2009A CNN is a dynamic nonlinear system with the local connectivity of cells and easy to be translated into a VLSI implementation. CNNs are very suitable for modeling the physical process of energy propagation since CNNs conserve the physical properties of a continuous structure. For the contour extraction, this paper proposes a method for establishing the
Xiao-Hua Liu, Da Yuan, Jinjiang Li 0001
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Texture-adaptive active contour models
2001Unsupervised segmentation is a key challenge for automated quantification of medical images. Although a balloon model is able to detect arbitrarily shaped objects in images, it requires careful adjustment of parameters prior to segmentation. Based on global texture analyses, our method allows to set these parameters automatically for heterogeneous ...
Thomas Martin Lehmann +2 more
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Automatic contour detection by encoding knowledge into active contour models
Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201), 2002An original method for an automatic detection of contours in difficult images is proposed. This method is based on a tight cooperation between a multi-resolution neural network and a hidden Markov model-enhanced dynamic programming procedure. This new method is able to overcome the three major drawbacks of the "standard" active contours, initialization
Olivier Gérard, Shérif Makram-Ebeid
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An active contour model for object tracking using the previous contour
Artificial Life and Robotics, 2003An active contour model is proposed for object tracking using prior information. Conventional algorithms have many problems when applied in object tracking. The proposed active contour algorithm, a model using an edge of an adapted color feature, not only modifies the internal energy function of the conventional algorithm to extend the search range and
Cheol-Taek Kim, Lee, JJ Lee, Ju-Jang
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Fast Implicit Active Contour Models
2002Implicit active contour models are widely used in image processing and computer vision tasks. Most implementations, however, are based on explicit updating schemes and are therefore of limited computational efficiency. In this paper, we present fast algorithms based on the semi-implicit additive operator splitting (AOS) scheme for both the geometric ...
Kühne, Gerald +3 more
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Learning Active Shape Models for Bifurcating Contours
IEEE Transactions on Medical Imaging, 2007Statistical shape models are often learned from examples based on landmark correspondences between annotated examples. A method is proposed for learning such models from contours with inconsistent bifurcations and loops. Automatic segmentation of tibial and femoral contours in knee X-ray images is investigated as a step towards reliable, quantitative ...
Matthias Seise +3 more
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