Kumar S Ray, Bimal Kumar Ray
Polygonal Approximation and Scale-Space Analysis of Closed Digital Curves
Kumar S Ray, Bimal Kumar Ray
Polygonal Approximation and Scale-Space Analysis of Closed Digital Curves
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This book covers the most important topics in the area of pattern recognition, object recognition, computer vision, robot vision, medical computing, computational geometry, and bioinformatics systems. Students and researchers will find a comprehensive treatment of polygonal approximation and its real life applications. The book not only explains
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This book covers the most important topics in the area of pattern recognition, object recognition, computer vision, robot vision, medical computing, computational geometry, and bioinformatics systems. Students and researchers will find a comprehensive treatment of polygonal approximation and its real life applications. The book not only explains
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Apple Academic Press
- Seitenzahl: 388
- Erscheinungstermin: 31. März 2021
- Englisch
- Abmessung: 234mm x 156mm x 20mm
- Gewicht: 544g
- ISBN-13: 9781774632642
- ISBN-10: 1774632640
- Artikelnr.: 69918632
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Apple Academic Press
- Seitenzahl: 388
- Erscheinungstermin: 31. März 2021
- Englisch
- Abmessung: 234mm x 156mm x 20mm
- Gewicht: 544g
- ISBN-13: 9781774632642
- ISBN-10: 1774632640
- Artikelnr.: 69918632
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
Kumar S. Ray, PhD, is a professor in the Electronics and Communication Science Unit at the Indian Statistical Institute, Kolkata, India. He has written a number of articles published in international journals and has presented at several professional meetings. His current research interests include artificial intelligence, computer vision, commonsense reasoning, soft computing, non-monotonic deductive database systems, and DNA computing. Bimal Kumar Ray is a professor at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He received his PhD degree in computer science from the Indian Statistical Institute, Kolkata, India. He received hs master's degree in applied mathematics from Calcutta University and his bachelor's degree in mathematics from St. Xavier's College, Kolkata. His research interests include computer graphics, computer vision, and image processing. He has published a number of research papers in peer-reviewed journals.
Polygonal Approximation: Introduction. A Split-and-Merge Technique. A
Sequential One-Pass Method. Another Sequential One-Pass Method. A
Data-Driven Method. Another Data-Driven Method. A Two-Pass Sequential
Method. Polygonal Approximation Using Reverse Engineering on Bresenham's
Line Drawing Technique. Polygonal Approximation as Angle Detection.
Polygonal Approximation as Angle Detection Using Asymmetric Region of
Support. Scale-space analysis: Introduction. Scale-Space Analysis and
Corner Detection on Chain Coded Curves. Scale-Space Analysis and Corner
Detection Using Iterative Gaussian Smoothing With Constant Window Size.
Corner detection using Bessel function as smoothing kernel. Adaptive
smoothing using convolution with Gaussian Kernel. Application of Polygonal
Approximation for Pattern Classification and Object Recognition:
Introduction. Polygonal Dissimilarity and Scale Preserving Smoothing
Matching Polygon Fragments. Polygonal Approximation to Recognize and Locate
Partially Occluded Objects: Hypothesis Generation and Verification
Paradigm. Object Recognition With Belief Revision: Hypothesis Generation
and Belief Revision Paradigm. Neuro-Fuzzy Reasoning for Occluded Object
Recognition: A Learning Paradigm Through Neuro-Fuzzy Concept. Conclusion.
Sequential One-Pass Method. Another Sequential One-Pass Method. A
Data-Driven Method. Another Data-Driven Method. A Two-Pass Sequential
Method. Polygonal Approximation Using Reverse Engineering on Bresenham's
Line Drawing Technique. Polygonal Approximation as Angle Detection.
Polygonal Approximation as Angle Detection Using Asymmetric Region of
Support. Scale-space analysis: Introduction. Scale-Space Analysis and
Corner Detection on Chain Coded Curves. Scale-Space Analysis and Corner
Detection Using Iterative Gaussian Smoothing With Constant Window Size.
Corner detection using Bessel function as smoothing kernel. Adaptive
smoothing using convolution with Gaussian Kernel. Application of Polygonal
Approximation for Pattern Classification and Object Recognition:
Introduction. Polygonal Dissimilarity and Scale Preserving Smoothing
Matching Polygon Fragments. Polygonal Approximation to Recognize and Locate
Partially Occluded Objects: Hypothesis Generation and Verification
Paradigm. Object Recognition With Belief Revision: Hypothesis Generation
and Belief Revision Paradigm. Neuro-Fuzzy Reasoning for Occluded Object
Recognition: A Learning Paradigm Through Neuro-Fuzzy Concept. Conclusion.
Polygonal Approximation: Introduction. A Split-and-Merge Technique. A
Sequential One-Pass Method. Another Sequential One-Pass Method. A
Data-Driven Method. Another Data-Driven Method. A Two-Pass Sequential
Method. Polygonal Approximation Using Reverse Engineering on Bresenham's
Line Drawing Technique. Polygonal Approximation as Angle Detection.
Polygonal Approximation as Angle Detection Using Asymmetric Region of
Support. Scale-space analysis: Introduction. Scale-Space Analysis and
Corner Detection on Chain Coded Curves. Scale-Space Analysis and Corner
Detection Using Iterative Gaussian Smoothing With Constant Window Size.
Corner detection using Bessel function as smoothing kernel. Adaptive
smoothing using convolution with Gaussian Kernel. Application of Polygonal
Approximation for Pattern Classification and Object Recognition:
Introduction. Polygonal Dissimilarity and Scale Preserving Smoothing
Matching Polygon Fragments. Polygonal Approximation to Recognize and Locate
Partially Occluded Objects: Hypothesis Generation and Verification
Paradigm. Object Recognition With Belief Revision: Hypothesis Generation
and Belief Revision Paradigm. Neuro-Fuzzy Reasoning for Occluded Object
Recognition: A Learning Paradigm Through Neuro-Fuzzy Concept. Conclusion.
Sequential One-Pass Method. Another Sequential One-Pass Method. A
Data-Driven Method. Another Data-Driven Method. A Two-Pass Sequential
Method. Polygonal Approximation Using Reverse Engineering on Bresenham's
Line Drawing Technique. Polygonal Approximation as Angle Detection.
Polygonal Approximation as Angle Detection Using Asymmetric Region of
Support. Scale-space analysis: Introduction. Scale-Space Analysis and
Corner Detection on Chain Coded Curves. Scale-Space Analysis and Corner
Detection Using Iterative Gaussian Smoothing With Constant Window Size.
Corner detection using Bessel function as smoothing kernel. Adaptive
smoothing using convolution with Gaussian Kernel. Application of Polygonal
Approximation for Pattern Classification and Object Recognition:
Introduction. Polygonal Dissimilarity and Scale Preserving Smoothing
Matching Polygon Fragments. Polygonal Approximation to Recognize and Locate
Partially Occluded Objects: Hypothesis Generation and Verification
Paradigm. Object Recognition With Belief Revision: Hypothesis Generation
and Belief Revision Paradigm. Neuro-Fuzzy Reasoning for Occluded Object
Recognition: A Learning Paradigm Through Neuro-Fuzzy Concept. Conclusion.