Wavelet moment invariants based on multiresolution image analysis

Hong Pan; LiangZheng Xia

doi:10.1117/12.538824

25 September 2003 Wavelet moment invariants based on image multiresolution image analysis

Hong Pan, LiangZheng Xia

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.538824
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

Abstract

A set of new invariant moment descriptors - wavelet moment invariants, which combine wavelet multiresolution analysis and moments invariants target recognition method, are proposed in this paper and their invariance also have been proved. Wavelet moment invariants take both advantages of the wavelet inherent property of multiresolution analysis and moment invariants quality of invariant to translation, scaling changes and rotation. Furthermore, studies of the effect of using different wavelet functions and their orders are carried out. Experimental results show that wavelet moment invariants derived from the wavelet function having proper vanishing moments, symmetry and compact support have the best discrimination performance.

Citation Download Citation

Hong Pan and LiangZheng Xia "Wavelet moment invariants based on image multiresolution image analysis", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.538824

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