PCA based forward-looking infrared airport recognition combining intensity and shape feature

Wei Liu; Jinwen Tian; Xinwu Chen

doi:10.1117/12.748373

15 November 2007 PCA based forward-looking infrared airport recognition combining intensity and shape feature

Wei Liu, Jinwen Tian, Xinwu Chen

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861I (2007) https://doi.org/10.1117/12.748373
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, a novel method based on PCA with shape and intensity information is proposed for infrared forward-looking airport recognition. Here, PCA is used to perform feature transformation and airport recognition. It maps an input image into a low-dimensional feature space in order to make the mapped features linearly separable. And the input image of conventional method only uses intensity information. The proposed method not only considers the intensity but also adopts shape-mask to emphasize the important object area information. The novel method is evaluated based on the sequence of infrared forward-looking airport images by using different airport recognition methods such as BP networking and SVM. The experiment's results have been compared based on percentage of correct classification, computation complexity and amount of training data, which show that this new method is superior to other recognition approach on computation complexity under almost the same recognition accuracy.

Citation Download Citation

Wei Liu, Jinwen Tian, and Xinwu Chen "PCA based forward-looking infrared airport recognition combining intensity and shape feature", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861I (15 November 2007); https://doi.org/10.1117/12.748373

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