A model-based approach to representation and matching of object shape patterns

Representation and matching of object shapes are two important steps of image analysis and computer vision applications. In most existing approaches, the object shapes for representation and matching are usually described in a ‘deterministic’ manner instead of in a ‘statistical’ form. In this paper,...

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Bibliographic Details
Published in:Pattern recognition letters 1992-10, Vol.13 (10), p.707-714
Main Authors: Chang, Yung-Liu, Leou, Jin-Jang
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
computer vision
Exact sciences and technology
image analysis
model-based approach
modified distance-weighted correlation map
Pattern recognition. Digital image processing. Computational geometry
Shape matching
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Summary:Representation and matching of object shapes are two important steps of image analysis and computer vision applications. In most existing approaches, the object shapes for representation and matching are usually described in a ‘deterministic’ manner instead of in a ‘statistical’ form. In this paper, a model-based approach to representation and matching of object shapes involving statistical properties is proposed. To speed up the matching process, a modified distance-weighted correlation (MDWC) map is constructed in the learning stage so that the matching between the input shape pattern T and its corresponding stored model shape pattern S can be performed without any correspondence. Some experimental results show the feasibility of the proposed approaches.
ISSN:0167-8655
1872-7344
DOI:10.1016/0167-8655(92)90100-E