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Bézier and Splines in Image Processing and Machine Vision de Sambhunath Biswas

Bézier and Splines in Image Processing and Machine Vision

Autor Sambhunath Biswas, Brian C. Lovell
en Limba Engleză Hardback – 9 ian 2008
Digital image processing and machine vision have grown considerably during the last few decades. Of the various techniques, developed so far, splines play a significant role in many of them. This book deals with various image processing and machine vision problems efficiently with splines and includes: the significance of Bernstein Polynomial in splines, detailed coverage of Beta-splines applications which are relatively new, Splines in motion tracking, various deformative models and their uses.
Finally the book covers wavelet splines which are efficient and effective in different image applications.
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Specificații

ISBN-13: 9781846289569
ISBN-10: 1846289564
Pagini: 268
Ilustrații: XVIII, 246 p. 73 illus.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.57 kg
Ediția:2008
Editura: SPRINGER LONDON
Colecția Springer
Locul publicării:London, United Kingdom

Public țintă

Research

Cuprins

Part I Early Background.- 1 Bernstein Polynomial and Bézier-Bernstein Spline.- Significance of Bernstein Polynomial in Splines.- 2 Image Segmentation.- Two Different Concepts of Segmentation.- Contour Based Segmentation.- Region Based Segmentation.- 3 1-d B-B Spline Polynomial and Hilbert Scan for Graylevel Image Coding.- Hilbert Scanned Image.- Shortcomings of Bernstein Polynomial and Error of Approximation.- 4 Image Compression.- SLIC: Sub-image Based Lossy Image Compression.- Part II Intermediate Steps.- 5 B-Splines and its Applications.- B-Spline Function.- 6 Beta-Splines: A Flexible Model.- Beta-Spline Curve.- 7 Discrete Spline and Vision.- Smoothing Discrete Spline and Vision.- Cardinal B-spline Basis and Riesz Basis.- 8 Spline Wavelets: Construction, Implication and Uses.- Cardinal B-spline Basis and Riesz Basis.- 9 Snakes and Active Contours.- Splines and Energy Minimisation Techniques.- Part III Advanced Methodologies.- 10 Globally Optimal Energy Minimisation Techinques.- Globally Minimal Surfaces (GMS).

Textul de pe ultima copertă

Digital image processing and machine vision have grown considerably during the last few decades. Of the various techniques, developed so far splines play a positive and significant role in many of them. Strong mathematical theory and ease of implementations is one of the keys of their success in many research issues.
This book deals with various image processing and machine vision problems efficiently with splines and includes:
• the significance of Bernstein Polynomial in splines
• effectiveness of Hilbert scan for digital images
• detailed coverage of Beta-splines, which are relatively new, for possible future applications
• discrete smoothing splines and their strength in application
• snakes and active contour models and their uses
• the significance of globally optimal contours and surfaces
Finally the book covers wavelet splines which are efficient and effective in different image applications.
Dr Biswas is a system analyst at the Indian Statistical Institute, Calcutta where he teaches Machine Vision in M Tech (Computer Science). His research interests include image processing, computer vision, computer graphics, pattern recognition, neural networks and wavelet image-data analysis.
Professor Lovell is a Research Leader in National ICT Australia and Research Director of the Intelligent Real-Time Imaging and Sensing Research Group at the University of Queensland. His research interests are currently focussed on optimal image segmentation, real-time video analysis and face recognition.

Caracteristici

Examines the various uses of splines in the area of Image Processing and Machine Vision Includes all significant splines as well as the latest one - the wavelet spline