Bézier And Splines In Image Processing And Machine Vision
Sambhunath Biswas,
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Add to basketSold by Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
AbeBooks Seller since April 17, 2013
Condition: New
Quantity: 5 available
Add to basketThis is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Seller Inventory # ABNR-1947
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.
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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