Scale-Space Theory in Computer Vision: 256 - Rilegato

Lindeberg, Tony

 
9780792394181: Scale-Space Theory in Computer Vision: 256

Sinossi

We perceive objects in the world as having structures at both coarse and fine scales. A tree, for instance, may appear as having a roughly round or cylindrical shape when seen from a distance, even though it is built up from a large number of branches. At a closer look, individual leaves become visible, and we can observe that they in turn have texture at an even finer scale. The fact that objects in the world appear in diffrent ways, depending upon the scale of observation, has important implications when analyzing measured data, such as images, with automatic methods. This work describes a formal framework, called "scale-space representation", for handling the notion of scale in image data. It gives an introduction to the general foundations of the theory and shows how it applies to essential problems in computer vision such as computation of image features and cues to surface shape. The subjects range from mathematical underpinning to practical computational techniques. The power of the methodology is illustrated by a set of examples.

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Recensione

` This approach will certainly turn out to be part of the foundations of the theory and practice of machine vision ... the author has no doubt performed an excellent service to many in the field of both artificial and biological vision. '
Jan Koenderink

Contenuti

1. Introduction and Overview. Part I: Basic Scale-Space Theory. 2. Linear Scale-Space and Related Multi-Scale Representations. 3. Scale-Space for 1-D Discrete Signals. 4. Scale-Space for N-D Discrete Signals. 5. Discrete Derivative Approximations with Scale-Space Properties. 6. Feature Detection in Scale-Space. Part II: The Scale-Space Primal Sketch: Theory. 7. The Scale-Space Primal Sketch. 8. Behaviour of Image Structures in Scale-Space: Deep Structure. 9. Algorithm for Computing the Scale-Space Primal Sketch. Part III: The Scale-Space Primal Sketch: Applications. 10. Detection Salient Blob-like Image Structures and their Scales. 11. Guiding Early Visual Processing with Qualitative Scale and Region. 12. Summary and Discussion. Part IV: Scale Selection and Shape Computation in a Visual Front-End. 13. Scale Selection for Differential Operators. 14. Direct Computation of Shape Cues by Scale-Space Operations. 15. Non-Uniform Smoothing. Appendix A: Technical Details. Bibliography. Index.

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