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18th International Conference on Pattern Recognition (ICPR'06) Volume 2
A Low-Complexity Deformation Invariant Descriptor
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
Li Tian, Waseda University
Sei-ichiro Kamata, Waseda University
In this paper, we propose a descriptor which is invariant to general deformations (only intensity locations change but not their value) by using Hilbert scanning. In our method, an image is converted to a 1-D sequence through Hilbert scanning at first. Then, we embed this sequence as a 1- D curve in the 2-D space. Because Hilbert scanning preserves the coherence in a 2-D image, it is easily to understand that the area under the curve is invariant to intensity location changes, naturally. Hence, we use some areas for an interest point as a deformation invariant descriptor. This descriptor can be computed in the 2-D space efficiently than other approaches where an image is embedded in the 3-D space or the dimensions of descriptors are very large. The experimental results show that our descriptor is low-complexity and superior to other approaches on interest point matching in deformation images.
Citation:
Li Tian, Sei-ichiro Kamata, "A Low-Complexity Deformation Invariant Descriptor," icpr, vol. 2, pp.227-230, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006
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