Preliminary study on ice crevasse texture analysis and recognition

Chunxia Zhou; Dongchen E; Zemin Wang

doi:10.1117/12.751177

15 November 2007 Preliminary study on ice crevasse texture analysis and recognition

Chunxia Zhou, Dongchen E, Zemin Wang

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67864D (2007) https://doi.org/10.1117/12.751177
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

The Antarctic is in very close relationship with the global climate, ecology environment, and the future of the human being. And it is unscientific to explore the Antarctic without any touch. While, crevasse is one of the most dangerous factors to the team members during the field expedition. Crevasse detection is very important in polar scientific research expedition for the safety; meanwhile, it is also meaningful information for ice flow monitoring. This paper presents the preliminary study on ice crevasse texture analysis and recognition based on SPOT image and coherence map derived from SAR image of Grove Mountains, east Antarctica. Since radar can penetrate the snow, it can detect the crevasse under the snow which can't be detected by optical satellite data. Based on the texture characteristics, gray level co-occurrence matrix is chosen at first to recognize the crevasse in SPOT image and coherence map respectively. And the results and the difference are analyzed. Optical and radar imagery both are valuable, however, there is no single sensor that gives 100 percent of the crevasses. Meanwhile, gray level co-occurrence matrix method can not detect the crevasse at 100 percent accuracy. More texture analysis method will be studied in further research.

Citation Download Citation

Chunxia Zhou, Dongchen E, and Zemin Wang "Preliminary study on ice crevasse texture analysis and recognition", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67864D (15 November 2007); https://doi.org/10.1117/12.751177

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