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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Umeyama, S. |
| Copyright Year | 1979 |
| Abstract | The problem of recognizing and localizing objects that can vary in parameterized ways is considered. To achieve this goal, a concept of parameterized point pattern is introduced to model parameterized families of such objects, and a parameterized point pattern matching algorithm is proposed. A parameterized point pattern is a very flexible concept that can be used to model a large class of parameterized objects, such as a pair of scissors with rotating blades. The proposed matching algorithm is formulated as a tree search procedure, and it generates all maximum matchings satisfying a condition called delta -boundedness. Several pruning methods based on the condition of delta -boundedness and their efficient computing techniques are given. The proposed matching algorithm is applied to a real shape matching problem in order to check the validity of the approach.< |
| Sponsorship | IEEE Computer Society |
| Starting Page | 136 |
| Ending Page | 144 |
| Page Count | 9 |
| File Size | 859451 |
| File Format | |
| ISSN | 01628828 |
| Volume Number | 15 |
| Issue Number | 2 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1993-02-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pattern matching Pattern recognition Shape Blades Computer vision Object recognition Information science |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software |
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