Graph Based Representations in Pattern Recognition

By: Jean-Michel Jolion (Editor), Walter Kropatsch (Editor)

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Paperback | 1 September 1998

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Paperback
160 Pages

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Annotated

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24.77 x 17.15 x 1.27

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Graph-based representation of images is becoming a popular tool since it represents in a compact way the structure of a scene to be analyzed and allows for an easy manipulation of sub-parts or of relationships between parts. Therefore, it is widely used to control the different levels from segmentation to interpretation. The 14 papers in this volume are grouped in the following subject areas: hypergraphs, recognition and detection, matching, segmentation, implementation problems, representation.

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You Can Find This Book In

Non-Fiction Mathematics Combinatorics & Graph Theory Computing & I.T.Computer Science Artificial Intelligence Computer Vision Pattern Recognition Databases Data Capture & Analysis Image Processing Digital Signal Processing (DSP)

Computer Programming & Software Development Algorithms & Data Structures Graphical & Digital Media Applications Gardening Engineering & Technology Other Technologies & Applied Sciences Applied Optics

Generalization of Two Hypergraphs. Algorithm of Calculation of the Greatest Sub-Hypergraph Common to Two Hypergraphs Annotated by Semantic Information	p. 1
Recognition of Polymorphic Patterns in Parameterized Graphs for 3D Building Reconstruction	p. 11
A Graph-Based Representation to Detect Linear Features	p. 21
Edge Detection as Finding the Minimum Cost Path in a Graph	p. 33
Subgraph Transformations for the Inexact Matching of Attributed Relational Graphs	p. 43
Efficient Graph Matching for Video Indexing	p. 53
Isomorphism between Strong Fuzzy Relational Graphs Based on k-Formulae	p. 63
A Graph Structure for Grey Value and Texture Segmentation	p. 73
Discrete Maps: a Framework for Region Segmentation Algorithms	p. 83
Image Sequence Segmentation by a Single Evolutionary Graph Pyramid	p. 93
Dual Graph Contraction with LEDA	p. 101
Implementing Image Analysis with a Graph-Based Parallel Computing Model	p. 111
The Frontier-Region Graph	p. 123
Optimization Techniques on Pixel Neighborhood Graphs for Image Processing	p. 135
Table of Contents provided by Blackwell. All Rights Reserved.

Graph Based Representations in Pattern Recognition

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Paperback

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