Bézier and Splines in Image Processing and Machine Vision

• Corporate Author: SpringerLink (Online service)
• Other Authors: Biswas, Sambhunath (Editor), Lovell, Brian C. (Editor)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2008.
• Subjects: Computer science.; Computer graphics.; Image processing.; Computer Science.; Image Processing and Computer Vision.; Computer Imaging, Vision, Pattern Recognition and Graphics.

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 man...

Table of Contents:

• 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).