A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
International Journal of Computer Vision
Topographic Maps and Local Contrast Changes in Natural Images
International Journal of Computer Vision
A Level Set Model for Image Classification
International Journal of Computer Vision
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
Journal of Mathematical Imaging and Vision
International Journal of Computer Vision
Level Set Based Segmentation with Intensity and Curvature Priors
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Topographic Maps of Color Images
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Learning to Detect Objects in Images via a Sparse, Part-Based Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Natural Image Statistics for Natural Image Segmentation
International Journal of Computer Vision
Image Parsing: Unifying Segmentation, Detection, and Recognition
International Journal of Computer Vision
International Journal of Computer Vision
Level Lines Selection with Variational Models for Segmentation and Encoding
Journal of Mathematical Imaging and Vision
Dynamical statistical shape priors for level set based sequence segmentation
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Shape preserving local histogram modification
IEEE Transactions on Image Processing
Fast computation of a contrast-invariant image representation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Wavelet-based level set evolution for classification of textured images
IEEE Transactions on Image Processing
Active contours for tracking distributions
IEEE Transactions on Image Processing
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A novel preferential image segmentation method is proposed that performs image segmentation and object recognition using mathematical morphologies. The method preferentially segments objects that have intensities and boundaries similar to those of objects in a database of prior images. A tree of shapes is utilized to represent the content distributions in images, and curve matching is applied to compare the boundaries. The algorithm is invariant to contrast change and similarity transformations of translation, rotation and scale. A performance evaluation of the proposed method using a large image dataset is provided. Experimental results show that the proposed approach is promising for applications such as object segmentation and video tracking with cluttered backgrounds.