Bézier and splines in image processing and machine vision
"Digital image processing machine vision have grown considerably during the last few decades. Of the various techniques developed so far, splines pay a positive and significant role in many of them. This book deals with various image processing and machine vision problems efficiently with splin...
| Main Author: | Biswas, Sambhunath. |
|---|---|
| Other Authors: | Lovell, Brian C., SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
London :
Springer,
©2008.
London : [2008] |
| Physical Description: |
1 online resource (xvii, 246 pages, 4 unnumbered pages of plates) : illustrations (some color) |
| Subjects: |
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).