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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 appr…
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. Readers will find a comprehensive treatment of polygonal approximation and its…
<STRONG>Part I: Polygonal Approximation </STRONG>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 Engineerin…
These 23 contributions focus on the most recent, developments in the rapidly evolving field of geometric invariants and their application to computer vision. The introduction summarizes the basics of invariant theory, discusses how invariants are related to problems in computer …
This book is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The Contributions include: ℗ʺ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ Morphological Image Analysis for Computer Vision Applications. ℗ʺ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ℗ℓ Meth…
This book is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The Contributions include: ℗ʺ℗ ℗ ℗ ℗ ℗ ℗ ℗ ℗ Morphological Image Analysis for Computer Vision Applications. ℗ʺ℗ ℗ ℗ ℗ ℗ ℗ ℗ ℗ Method…
"This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as th…
Markov random fields for vision and image processing
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Type: Book