DocumentCode :
1346806
Title :
Extension of dynamic link matching by introducing local linear maps
Author :
Aonishi, Toru ; Kurata, Koji
Author_Institution :
Dept. of Syst. & Human Sci., Osaka Univ., Japan
Volume :
11
Issue :
3
fYear :
2000
fDate :
5/1/2000 12:00:00 AM
Firstpage :
817
Lastpage :
822
Abstract :
It is well known that dynamic link matching (DLM) is a flexible pattern matching model tolerant of deformation or nonlinear transformation. However, previous models cannot treat severely deformed data pattern in which local features do not have their counterparts in a template pattern. We extend DLM by introducing local linear maps (LLMs). Our model has a reference vector and an LLM for each lattice point of a data pattern. The reference vector maps the lattice point into a template pattern and the LLM carries the information regarding how the local neighborhood is mapped. Our model transforms local features by LLMs in a data pattern and then matches them with their counterparts in a template pattern. Therefore, our model is adaptable to larger transformations. For simplicity, we restricted LLMs to rotations. Neighboring LLMs are diffusionally coupled with each other. The model is numerically demonstrated to be very flexible in dealing with deformation and rotation compared to previous models. The framework of our model can be easily extended to models with more general LLMs (expansion, contraction, and so on)
Keywords :
feature extraction; filtering theory; pattern matching; contraction; deformation; dynamic link matching; expansion; flexible pattern matching model; lattice point; local features; local linear maps; local neighborhood; rotation; Cost function; Data mining; Deformable models; Feature extraction; Gabor filters; Lattices; Numerical models; Pattern matching; Pattern recognition; Vectors;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.846754
Filename :
846754
Link To Document :
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