On the Detection of the Axes of Symmetry of Symmetric and Almost Symmetric Planar Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of VLSI Signal Processing Systems
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
The Intensity Axis of Symmetry and Its Application to Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Radial Symmetry Transform for Detecting Points of Interest
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Layered "Recognition Cone" Networks That Preprocess, Classify, and Describe
IEEE Transactions on Computers
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Pyramid computation is a natural paradigm of computation in planning strategies and multi-resolution image analysis. This paper introduces a new paradigm that is based on the concept of soft-hierarchical operators implemented in a pyramid architecture to retrieve global versus local symmetries. The concept of symmetry is mathematically well defined in geometry whenever patterns are crisp images (two levels). Necessity for a soft approach occurs whenever images are multi-levels and the separation between object and background is subjective or not well defined. The paper describes a new pyramid operator to detect symmetries and shows some experiments supporting the approach. This work has been partially supported by the French Ministry of Research and the University Paris XI and the Agenzia Spaziale Italiana.