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Proceedings Paper

Infrared image object recognition based on invariant contourlet sub-band features
Author(s): Xue Mei; Liangzheng Xia; Jinguo Lin
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Paper Abstract

A novel feature descriptor-contourlet Fourier invariant feature, which combine contourlet decomposition and Fourier transforms and is translation-, rotation-, and scale-invariant, is put forward in this paper. Firstly, the translation and rotation invariant are achieved by Fourier transform along the circles that around the mass center of the scale-normalized target. Then statistic parameters of General Gaussian density (GGD) model of each contourlet sub-bands are evaluated. GGD parameters and contourlet decomposition coefficients are both as the features, which not only with rotation, shift and scaling invariant, but also with the contourlet inherent property of multi-resolution, local and multi-direction. We present experimental results using this descriptor in infrared image recognition, and it shows this descriptor is a good choice for object recognition.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861N (15 November 2007); doi: 10.1117/12.748584
Show Author Affiliations
Xue Mei, Nanjing Univ. of Technology (China)
Southeast Univ. (China)
Liangzheng Xia, Southeast Univ. (China)
Jinguo Lin, Nanjing Univ. of Technology (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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