Bézier and Splines in Image Processing and Machine Vision
Contributor(s): Biswas, Sambhunath [editor.] | Lovell, Brian C [editor.] | SpringerLink (Online service).
Material type:
BookPublisher: London : Springer London, 2008.Description: XVIII, 246 p. 73 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781846289576.Subject(s): Computer science | Computer graphics | Image processing | Computer Science | Image Processing and Computer Vision | Computer Imaging, Vision, Pattern Recognition and GraphicsDDC classification: 006.6 | 006.37 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
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PK Kelkar Library, IIT Kanpur | Available | EBK3063 |
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).
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.
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