Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary Finding with Parametrically Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
A Level Set Model for Image Classification
International Journal of Computer Vision
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
A level set algorithm for minimizing the Mumford-Shah functional in image processing
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
International Journal of Computer Vision
IEEE Transactions on Image Processing
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In detecting the boundary of an object in an image, if certain prior shape knowledge of the object is available, an effective approach is to have the intensity gradient information in the image and the prior shape knowledge be combined together to drive an active contour for the purpose. While in the classical methods the two terms are almost always summed with a certain weight between them to form the optimization functional, in the method we propose, they are multiplied together so as to avoid the need and thus design of the weight parameter. We show that the object detection result in the traditional formulation could indeed be very much affected by the weight value, and the proposed method, being without its presence, is therefore free from the influence of the important parameter. Experimental results on cells in real biological images, whose boundaries are blurred to very different degrees across the image by the inevitably uneven illumination, are shown to demonstrate the improvement in performance.