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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Demirci, M.F. |
| Copyright Year | 2010 |
| Abstract | Indexing into large database systems is essential for a number of applications. This paper presents a new indexing structure, which overcomes an important restriction of a previous indexing technique using a recently developed theorem from the domain of matrix analysis. Specifically, given a set of distance values computed by distance function, which do not necessarily satisfy the triangle inequality, this paper shows that computing its nearest distance values that obey the properties of a metric enables us to overcome the limitations of the previous indexing algorithm. We demonstrate the proposed framework in the context of a recognition task. |
| Starting Page | 3057 |
| Ending Page | 3060 |
| File Size | 516583 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424475421 |
| ISSN | 10514651 |
| e-ISBN | 9781424475414 |
| DOI | 10.1109/ICPR.2010.749 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-23 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Shape Measurement Indexing Linear matrix inequalities Horses Electric shock Metric Nearness Partial Matching Shape Recognition |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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