Invariant image matching by compacting and moment normalization
作者:
Wen‐Hao Wang,
Yung‐Chang Chen,
期刊:
Journal of the Chinese Institute of Engineers
(Taylor Available online 1998)
卷期:
Volume 21,
issue 6
页码: 719-730
ISSN:0253-3839
年代: 1998
DOI:10.1080/02533839.1998.9670430
出版商: Taylor & Francis Group
关键词: invariant matching;skewing;compacting;moment normalization
数据来源: Taylor
摘要:
A new approach is proposed in this paper for image matching an invariant to translation, rotation, anisotropic scaling, and skewing. A compact image is acquired by principal component analysis and rescaling the image on the principal axes. However, the direction of the principal axis is susceptible to the skewing effect, which will bring about the failure of the orientation normalization. In addition, overall scale normalization is not taken into consideration. Hence, the central idea of this paper is to find the normalized orientation and overall scale for the compact image by virtue of the moment normalization. In consequence, the resultant image becomes thoroughly normalized and can be directly employed for matching by simple similarity metrics. Alternatively, for the purpose of fast matching, two 1‐D projected results are evaluated for matching. These are undoubtly faster than the conventional pixel‐based correlation.
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