Paper
15 November 2007 Infrared image object recognition based on invariant contourlet sub-band features
Xue Mei, Liangzheng Xia, Jinguo Lin
Author Affiliations +
Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861N (2007) https://doi.org/10.1117/12.748584
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xue Mei, Liangzheng Xia, and Jinguo Lin "Infrared image object recognition based on invariant contourlet sub-band features", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861N (15 November 2007); https://doi.org/10.1117/12.748584
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Transform theory

Infrared imaging

Infrared radiation

Fourier transforms

Image filtering

Feature extraction

Object recognition

Back to Top