Study on Aircraft Recognition in High Spatial Resolution Remote Sensing Image Based on Skeleton Characteristics Analysis

Abstract:

Aircraft recognition automatically is an important research content in target recognition. Improving aircraft recognition precision can accurately realize the regional dynamics, and make correct decision-making support. This paper researches on recognition of aircraft in high spatial resolution remote sensing imagery based on edge detection technology, extraction skeleton technology based on Constrained Delaunay Triangulation, and target recognition technology based on Geometric Features Parameter and Network Measurement.

• Periodical: Advanced Materials Research (Volumes 268-270)
• Pages: 1982-1985
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.268-270.1982
• Online since: July 2011
• Authors: Dong Cai
• Keywords: Aircraft Extraction, Geometric Features Parameter, High Spatial Resolution Remote Sensing Image, Network Measurement, Skeleton Characteristics

References

[1] K. Li, R. WANG, C. WANG. A Method of Tree Classifier for the Recognition of Airplane Types[J]. Computer Engineering & Science, 2006, 11: 136-139.

[2] K. Xu. Recognition of Remote Sensing Target Based on Wavelet Transform and Support Vector Machine[J]. Computer & Digital Engineering, 2007(7): 123-125.

[3] Y. Hu, S. Wang, B. Hou, L. Jiao. REMOTE SENSING TARGET RECOGNITION BASED ON SWBCT AND PROJECTION FEATURE[J]. Journal of Infrared and Millimeter Waves, 2007(6): 51-455.

[4] J.H. Xu. Mathematics Method of Modern Geography[M]. Higher Education Press, (2002).

[5] P. Hu, H. Wang, C. Shao. Polygon Medial Axis Problem and the Algorithm[J]. Editorial Board of Geomatics and Information Science of Wuhan University, 2005(10): 853-857.

[6] F. Chin, J. Snoeyink, C.A. Wang. Finding the Medial Axis of a Simple Polygon in Linear Time. London: Springer-Verlag, (1995).

[7] Z.L. Li, Q. Zhu. Digital Elevation Mode[M]. Wuhan University Press, (2001).

[8] T.H. Ai, R.Z. Guo. Extracting Center-lines and Building Street Network Based on Constrained Delaunay Triangulation[J]. ACTA GEODAETICA ET CARTOGRAPHIC SINICA, 2000(4): 348-354.

[9] L.M. Huang, Y.P. Zhang. The Automatic Create Method of Framework Lines of Area by Trianglated Network[J]. Journal of The Pla Institute of Surveying and Mapping, 2002(4): 262-264.

[10] P.H. Swain, H. Hauska. The decision tree classifier design and potential [J]. Proceedings of IEEE, 1977, GE_15(3): 142~147.

DOI: 10.1109/tge.1977.6498972

[11] J. Yang, Z.M. Zhao, J. Yang. A Shadow Removal Method for High Resolution Remote Sensing Image[J]. Geomatics and Information Science of Wuhan University, 2008(1): 17-20.

[12] Y. Li, T. Sasagawa, P. Gong. A System of the Shadow Detection and Shadow Removal for High Resolution City Aerial Photo[C]. ISPRS, Commission Ⅲ, Istanbul, (2004).

[13] M.N. Do, M. Vetterli. Contour lets: adirectional multi-resolution image representation [C]. International Conference on Image Processing, 2002 (1), 357-360.

[14] B. Bhanu, P. Jing. Adaptive integrated image segmentation and object recognition [J]. IEEE Transactions on Systems, Man and ybernetics_Part C, 2000, 30(4): 427~441.

DOI: 10.1109/5326.897070

[15] N. Halem. Contextual, Image Understanding of Airport Piotographs, SPIE, 1981: 1521-1532.