A Fast Algorithm for Road Recognition in Remote Sensing Image

Li Li Li; Yong Xin Liu

doi:10.4028/www.scientific.net/AMR.108-111.1344

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 108-111A Fast Algorithm for Road Recognition in Remote...

A Fast Algorithm for Road Recognition in Remote Sensing Image

Abstract:

In general, the road extraction methods in remote sensing images mainly are edge detection, feature integration, and so on. A fast road recognition arithmetic is presented in this paper. First using adaptive binarization arithmetic, the path on remote sensing images is extracted. Then morphological method is used to process image. Finally, the extracted image superimposed with the original and get clear road. Simulation results shows that this algorithm is efficiency, the anti-noise ability is enhance, and more precision.

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Periodical:

Advanced Materials Research (Volumes 108-111)

Pages:

1344-1347

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.108-111.1344

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Online since:

May 2010

Authors:

Li Li Li, Yong Xin Liu

Keywords:

Adaptive Binarization, Morphological Operate, Remote Sensing Image, Road Extraction

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References

[1] Yoon C.R., Kim K.Y., Kim H.G., and Kim K.O.: Morphological transformation for remote sensed image using fuzzy theory. The 6 th World multi conference on systemic, cybernetics and informatics, Proceedings - image, acoustic, speech and signal processing II, Vol. 9 (2002).

Google Scholar

[2] Navon, Y.: Layer - based binarization for textual Images. 19 th International conference on pattern recognition, Vol. 1-6, (2008), pp.2634-2638.

DOI: 10.1109/icpr.2008.4761836

Google Scholar

[3] Guo R., Li D.L.: Road detection method for land consolidation using mathematical morphology from high resolution image. Applied and computational mathematics, 2 nd, (2008), pp.309-314.

Google Scholar

[4] Soille, P.: Morphological image compositing. Pattern analysis and machine intelligence, IEEE transactions, Vol. 28, No. 5, (2006), pp.673-683.

DOI: 10.1109/tpami.2006.99

Google Scholar

[5] Bao H.G., Jiang Y.: Research on segmentation method in digital image processing. Proceedings of 1st international conference of modeling and simulation, Vol. 3 - modeling and simulation in electronics, computing, and bio-medicine, (2008).

Google Scholar