Land Cover Recognition using Min-Cut/Max-Flow Segmentation and Orthoimages

Authors

  • Sergejs Kodors Rezekne Higher Education Institution (LV)

DOI:

https://doi.org/10.17770/etr2015vol3.171

Keywords:

land cover, min-cut/max-flow segmentation, orthoimage, recognition

Abstract

The geospatial information is significant for many socio-technical activities like urban planning, the prediction of natural hazards, the monitoring of land use, weather forecasting, cadastral surveys etc. It is possible to acquire geospatial information from a distance using remote sensing technologies, but remotely sensed images don’t have semantics without a previous recognition. The classification of geospatial information is expensive and time consuming process. The paper describes the automatic land cover recognition method, which is based on min-cut/max-flow segmentation. The raw data are othoimages with a high resolution. The proposed method is tested and evaluated by Cohen’s kappa coefficient.

Downloads

Download data is not yet available.

References

Yongwel Sheng, Peng Gong and Gregory S., “Biging.True Orthoimage Production for Forested Areas from Large-Scale Aerial Photographs,” American Society for Photogrammetry and Remote Sensing, Photogrammetric Engineering & Remote Sensing, Vol. 69, No. 3, pp. 259-266, March 2003.

Fahmi Amhar, Josef Jansa and Christine Ries., “The Generation of True Orthophotos using a 3D Building Model in Conjunction with a Conventional DTM,” IAPRS, Vol. 32, Part 4, pp. 16-22, 1998.

T. Veljanovski, U. Kanjir and K. Ostir., “Object-based image analysis of remote sensing data,” Geodetski Vestnik, vol. 55, no. 4, pp. 678-688, 2011.

Y. Babykalpana and K. ThanushKodi., “Classification of land use land cover change detection using remotely sensed data,” International Journal on Computer Science and Engineering (IJCSE), Vol. 3, no. 4, pp. 1638-1644, 2011.

Military Memorial Park, Pákozd, “The world's highest spatial resolution aerial orthophoto map produced by aeroplane,” Military Memorial Park, Pákozd. [Online]. Available: www.aerialrecord.com. [Accessed 05.04.2013].

S. S. Al-amri, N. V. Kalyankar and S. D. Khamitkar, “Image Segmentation by using Edge Detection,” International Journal on Computer Science and Engineering, Vol. 2, pp. 804-807, 2010.

Y. Ramadevi, T. Sridevi, B. Poornima and B. Kalyani, “Segmentation and object recognition using edge detection techniques,” International Journal of Computer Science & Information Technology (IJCSIT), Vol. 2, no. 6, pp. 153-161, December 2010.

Sergejs Kodors and Imants Zarembo, Urban Objects Segmentation Using Edge Detection, Environment. Technology. Resources, Proceedings of the 9th International Scientific and Practical Conference. Vol. 2, pp. 26-29, 2013.

G. Ignatov, H. Nikolov, D. Petkov and G. Georgie, ”Segmentation of satellite images by means of morphological and object-oriented approaches,” International Society of Photogrammetry and Remote Sensing (ISPRS), Vol. 36, part 7, p. 4, May 2006.

Mohamad Awad, Kacem Chehdi and Ahmad Nasri, “Multicomponent Image Segmentation Using a Genetic Algorithm and Artificial Neural Network,” IEEE Geoscience and Remote Sensing Letters, Vol. 4, No. 4, pp. 571-575, October 2007.

Zhenyu Wu and Richard Leahy, “An Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image Segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 11, pp. 1101-1113, November 1993.

Vladimir Kolmogorov and Ramin Zabih, “What Energy Functions Can Be Minimized via Graph Cuts?,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 2, pp. 147-159, February 2004.

Yuri Boykov and Vladimir Kolmogorov, “An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 9, pp. 1124-1137, September 2004.

Yury Boykov and Gareth Funka-Lea, “Graph Cuts and Efficient N-D Image Segmentation,” International Journal of Computer Vision, Vol. 70, No. 2, pp. 109–131, 2006.

Andrew Delong, Anton Osokin, Hossam N. Isack and Yuri Boykov, “Fast Approximate Energy Minimization with Label Costs,” International Journal of Computer Vision, Vol. 96, no. 1, pp. 1–27, January 2012.

Sergejs Kodors and Imants Zarembo, Land Cover Recognition with Logical Reasoning using Orthophoto Images, RCITD 2013, Proceeding of the 1st Research Conference In Technical Disciplines, pp. 116-120, November 2013.

R. G. Congalton, “A review of assessing the accuracy of classifications of remotely sensed data”, remote sens. environ., Vol. 37, pp. 35-46, 1991.

Downloads

Published

2015-06-16

How to Cite

[1]
S. Kodors, “Land Cover Recognition using Min-Cut/Max-Flow Segmentation and Orthoimages”, ETR, vol. 3, pp. 127–133, Jun. 2015, doi: 10.17770/etr2015vol3.171.