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Graph-based representations and techniques for image processing and image analysis
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DOI：10.1016/S0031-3203(01)00066-8.png)
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摘要
En 中文
In this paper we will discuss the use of some graph-based representations and techniques for image processing and analysis, Instead of making an extensive review of the graph techniques in this field, we will explain how we are using these techniques in an active vision system for an autonomous mobile robot developed in the Institut de Robotica i Informatica Industrial within the project Active Vision System with Automatic Learning Capacity for Industrial Applications (CICYT TAP98-0473). Specifically we will discuss the use of graph-based representations and techniques for image segmentation, image perceptual grouping and object recognition. We first present a generalisation of a graph partitioning greedy algorithm for colour image segmentation. Next we describe a novel fusion of colour-based segmentation and depth front stereo that yields a graph representing every object in the scene. Finally we describe a new representation of a set of attributed graphs (AGs), denominated function-described graphs (FDGs), a distance measure for matching AGs with FDGs and some applications for robot vision. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Keyword:
structural pattern recognition
graph-based representations
object recognition
colour image segmentation
perceptual grouping
data fusion
depth from stereo
attributed graphs
function-described graphs
distance measure between graphs
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期刊
IF:
7.6
论文数:
1.3W
被引数:
4.5W
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