Object matching algorithms using robust Hausdorff distance measures

A Hausdorff distance (HD) is one of commonly used measures for object matching. This work analyzes the conventional HD measures and proposes two robust HD measures based on m-estimation and least trimmed square (LTS) which are more efficient than the conventional HD measures. By computer simulation,...

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Bibliographic Details
Published inIEEE transactions on image processing Vol. 8; no. 3; pp. 425 - 429
Main Authors SIM, D.-G, KWON, O.-K, PARK, R.-H
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.03.1999
Institute of Electrical and Electronics Engineers
Subjects
Algorithms
Applied sciences
Computer simulation
Computer vision
Euclidean distance
Exact sciences and technology
High definition video
Image analysis
Image processing
Information, signal and communications theory
Matching
Object recognition
Robustness
Signal processing
Size measurement
Statistics
Telecommunications and information theory
Two dimensional displays
Hausdorff dimension
Distance measurement
Computer simulation
Image processing
M estimation
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Summary:A Hausdorff distance (HD) is one of commonly used measures for object matching. This work analyzes the conventional HD measures and proposes two robust HD measures based on m-estimation and least trimmed square (LTS) which are more efficient than the conventional HD measures. By computer simulation, the matching performance of the conventional and proposed HD measures is compared with synthetic and real images.
Bibliography:ObjectType-Article-2
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ISSN:1057-7149
1941-0042
DOI:10.1109/83.748897