DocumentCode
457154
Title
A Low-Complexity Deformation Invariant Descriptor
Author
Li Tian ; Kamata, Sei-ichiro
Author_Institution
Graduate Sch. of Info., Waseda Univ., Kitakyushu
Volume
2
fYear
0
fDate
0-0 0
Firstpage
227
Lastpage
230
Abstract
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 1D sequence through Hilbert scanning at first. Then, we embed this sequence as a 1D curve in the 2D space. Because Hilbert scanning preserves the coherence in a 2D 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 2D space efficiently than other approaches where an image is embedded in the 3D 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
Keywords
image matching; image morphing; Hilbert scanning; intensity location changes; interest point matching; low-complexity deformation invariant descriptor; Computational complexity; Data analysis; Embedded computing; Hilbert space; Image coding; Image converters; Image matching; Image retrieval; Image sampling; Object recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.91
Filename
1699188
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