Automatic recognition of airport in remote sensing images based on improved methods

Yan Chen; Kaimin Sun; Jingxiong Zhang; Zongjian Lin

doi:10.1117/12.750872

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15 November 2007 Automatic recognition of airport in remote sensing images based on improved methods

Yan Chen, Kaimin Sun, Jingxiong Zhang, Zongjian Lin

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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678645 (2007) https://doi.org/10.1117/12.750872
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Airport recognition remains an important and challenging topic for research. In general, there are four main steps in the process of airport recognition: pre-processing of remote sensing images, features extraction, rough location and the recognition of airport. This paper puts forward an automatic airport recognition method which adopts improved methods in each step. In pre-processing, an edge-preserve image smoothing algorithm based on Convexity Model is developed. In features extraction, the Canny operator and chain codes are used. An improved Κ-Means lines segmentation and estimate rules are used to find candidate areas in rough location of the airport. And those candidate regions are binarized and prior knowledge is used in airport recognition. Experimental data and application results show that the above methods are efficient and enhance the accuracy in airport recognition.

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Yan Chen, Kaimin Sun, Jingxiong Zhang, and Zongjian Lin "Automatic recognition of airport in remote sensing images based on improved methods", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678645 (15 November 2007); https://doi.org/10.1117/12.750872

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