The problem of scale pervades both the natural sciences and the vi sual arts. The earliest scientific discussions concentrate on visual per ception (much like today!) and occur in Euclid's (c. 300 B. C. ) Optics and Lucretius' (c. 100-55 B. C. ) On the Nature of the Universe. A very clear account in the spirit of modern "scale-space theory" is presented by Boscovitz (in 1758), with wide ranging applications to mathemat ics, physics and geography. Early applications occur in the cartographic problem of "generalization", the central idea being that a map in order to be useful has to be a "generalized" (coarse grained) representation of the actual terrain (Miller and Voskuil 1964). Broadening the scope asks for progressive summarizing. Very much the same problem occurs in the (realistic) artistic rendering of scenes. Artistic generalization has been analyzed in surprising detail by John Ruskin (in his Modern Painters), who even describes some of the more intricate generic "scale-spacesin gularities" in detail: Where the ancients considered only the merging of blobs under blurring, Ruskin discusses the case where a blob splits off another one when the resolution is decreased, a case that has given rise to confusion even in the modern literature.
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` 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
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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Hardcover. Condizione: new. Hardcover. 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. The fact that objects in the world appear in different ways 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780792394181
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