A thinning algorithm by contour generation
Communications of the ACM
Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulating the Grassfire Transform Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Sequential Algorithms for a Generalized Distance Transformation Based on Minkowski Operations
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Generation of Skeletons from Discrete Euclidean Distance Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Decomposition of Multiscale Skeletons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary Smoothing via Symmetry Transforms
Journal of Mathematical Imaging and Vision
Tracking Deformable Objects in the Plane Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Intensity Axis of Symmetry and Its Application to Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symmetry Maps of Free-Form Curve Segments via Wave Propagation
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
A neural architecture for the symmetric-axis transform
Neurocomputing
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This paper presents a new algorithm to compute skeletons of noisy images of objects which can be described as ``amorphous blobs.'' Such a requirement arose from our research to obtain a better understanding of the role of the pseudopod in leukocyte locomotion. It involves the modeling and detection of pseudopods which are by their nature nonrigid bodies appearing on the cell's surface membrane. By computing skeletons at different resolutions, a filtered version can be produced without violating the constraints imposed by the semantic knowledge of pseudopod morphology. The filtered version incorporates all the significant ``events'' that occur at the different resolutions. The resolution at which the shape is examined is related to the degree of smoothing, in that the lower the resolution gets, the higher the degree of smoothing. Skeleton branches that persist over several scales arise from convexities that are locally as well as globally significant. Their stability is related to their perceptual significance. Our approach is to combine an initial region centered description (skeleton) with a boundary analysis executed at different resolutions. Having computed the skeleton at different scales, we then use those computed at the lower resolutions as a measure of how global the underlying convexity is. Clearly the skeletons computed at higher resolutions represent the exact location and orientation of the underlying convexities.