Peter J. Olver / Allen Tannenbaum (eds.)

Mathematical Methods in Computer Vision

Herausgegeben:Olver, Peter J.; Tannenbaum, Allen

• Gebundenes Buch

Produktbeschreibung

This volume comprises some of the key work presented at two IMA

Workshops on Computer Vision during fall of 2000. Recent years have

seen significant advances in the application of sophisticated

mathematical theories to the problems arising in image processing.

Basic issues include image smoothing and denoising, image enhancement,

morphology, image compression, and segmentation (determining

boundaries of objects-including problems of camera distortion and

partial occlusion). Several mathematical approaches have emerged,

including methods based on nonlinear partial differential equations,

stochastic and statistical methods, and signal processing techniques,

including wavelets and other transform theories.

Shape theory is of fundamental importance since it is the bottleneck

between high and low level vision, and formed the bridge between the

two workshops on vision. The recent geometric partial differential

equation methods have been essential in throwing new light on this

very difficult problem area. Further, stochastic processes, including

Markov random fields, have been used in a Bayesian framework to

incorporate prior constraints on smoothness and the regularities of

discontinuities into algorithms for image restoration and

reconstruction.

A number of applications are considered including optical character

and handwriting recognizers, printed-circuit board inspection systems

and quality control devices, motion detection, robotic control by

visual feedback, reconstruction of objects from stereoscopic view

and/or motion, autonomous road vehicles, and many others.

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Produktdetails

• The IMA Volumes in Mathematics and its Applications 133
• Verlag: Springer / Springer New York / Springer, Berlin
• Artikelnr. des Verlages: 978-0-387-00497-6
• 2003 edition
• Seitenzahl: 156
• Erscheinungstermin: 1. Oktober 2003
• Englisch
• Abmessung: 243mm x 162mm x 14mm
• Gewicht: 412g
• ISBN-13: 9780387004976
• ISBN-10: 0387004971
• Artikelnr.: 12300753

Inhaltsangabe

A large deviation theory analysis of Bayesian tree search.- Expectation-based, multi-focal, saccadic vision (understanding dynamic scenes observed from a moving platform).- Statistical shape analysis in high-level vision.- Maximal entropy for reconstruction of back projection images.- On the Monge-Kantorovich problem and image warping.- Analysis and synthesis of visual images in the brain: evidence for pattern theory.- Nonlinear diffusions and optimal estimation.- The Mumford-Shah functional: from segmentation to stereo.- List of workshops participants.