Research Article

Automatic Road Extraction based on Normalized Cuts and Level set Methods

by  M.Rajeswari, K.S.Gurumurthy, L.Pratap Reddy, S.N.Omkar, Senthilnath.J
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 18 - Issue 7
Published: March 2011
Authors: M.Rajeswari, K.S.Gurumurthy, L.Pratap Reddy, S.N.Omkar, Senthilnath.J
10.5120/2298-2988
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M.Rajeswari, K.S.Gurumurthy, L.Pratap Reddy, S.N.Omkar, Senthilnath.J . Automatic Road Extraction based on Normalized Cuts and Level set Methods. International Journal of Computer Applications. 18, 7 (March 2011), 10-16. DOI=10.5120/2298-2988

                        @article{ 10.5120/2298-2988,
                        author  = { M.Rajeswari,K.S.Gurumurthy,L.Pratap Reddy,S.N.Omkar,Senthilnath.J },
                        title   = { Automatic Road Extraction based on Normalized Cuts and Level set Methods },
                        journal = { International Journal of Computer Applications },
                        year    = { 2011 },
                        volume  = { 18 },
                        number  = { 7 },
                        pages   = { 10-16 },
                        doi     = { 10.5120/2298-2988 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2011
                        %A M.Rajeswari
                        %A K.S.Gurumurthy
                        %A L.Pratap Reddy
                        %A S.N.Omkar
                        %A Senthilnath.J
                        %T Automatic Road Extraction based on Normalized Cuts and Level set Methods%T 
                        %J International Journal of Computer Applications
                        %V 18
                        %N 7
                        %P 10-16
                        %R 10.5120/2298-2988
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic road network extraction based on high resolution satellite image for urban planning holds great potential for significant reduction of database development/updating cost and turnaround time. Satellite remote sensing has been recognized worldwide as an effective technology for the monitoring and mapping the urban development. Two approaches for road network extraction for an urban region have been proposed. When an image is considered in original form it is difficult and computationally expensive to extract roads due to presence of other road-like features with straight edges. Hence roads are first extracted as elongated regions by removing bright regions (that mostly represent the buildings, parking lots and other open spaces), non-linear noise segments are removed median filtering (based upon the fact that road networks constitute large number of small linear structures).The roads are then modeled as boundaries and are extracted using Level set and Normalized cuts methods .Finally The extracted roads are overlayed on the original image. The experimental results show that these approaches are efficient in extracting road segments in urban region from high resolution satellite images. Evaluation of the results carried out by comparing the level set and normalized cuts results with manually extracted reference data. The methods were applied on the high resolution IKONOS image of urban area of Hobart, Australia.

References
  • Zhang, C., 2004. Towards an operational system for automated updating of road databases by integration of imagery and geodata. ISPRS J. .Photogramm. 58(3-4), 2004 pp. 166-186
  • Mena, J.B. and Malpica, J.A., 2005. An automatic method for road extraction in rural and semi-urban areas starting from high resolution satellite imagery. Pattern Recogn. Lett. 26(9), 2005pp.1201-1220.
  • Gerke, M. and Heipke, C., 2008. Image-based quality assessment of road databases. Int. J. Geogr. Inf. Sci., 22(8), 2008 pp.871-894.
  • Baumgartner, A., Steger, C., Mayer, H., Eckstein, W. and Ebner, H., 1999. Automatic road extraction based on multiscale, grouping, and context. Photogramm. Eng. Rem. S. 65(7), 1999pp. 777-785
  • Zhang, Q. and Couloigner, I., 2006. Automated road network extraction from high resolution multi-spectral imagery. In: Proc.ASPRS Annual Conf., Reno, Nevada, 200610 p.
  • Hu X, Tao CV and Hu Y (2004) Automatic Road Extraction from dense urban area by integrated processing of high-resolution imagery and lidar data. XXth ISPRS Congress, Istanbul, 12–23 July 2004. (Available online at: http://www.isprs.org/istanbul2004/comm3/papers/288.pdf- International archives of photogrammetry and Remote Sensing, Vol. XXXIII, part B3. Amsterdam
  • Doucette, P., Agouris, P., Stefanidis, A. and Musavi, M., 2001.Self-organized clustering for road extraction in classifiedimagery. ISPRS J. Photogramm. 55(5-6), 2001 pp. 347-358
  • Hu, J., Razdan, A., Femiani, J.C., Cui, M. and Wonka, P., 2007.Road network extraction and intersection detection from aerial images by tracking road footprints. IEEE TGARS 45(12), 2007 pp.4144-4156
  • Bacher, U. and Mayer, H. Automatic road extraction from multispectral high resolution satellite images. In. Stilla U, Rottensteiner F, Hinz S (Eds) CMRT05. IAPRS, Vol. XXXVI, Part 3/W24, Vienna, Austria. 2005.
  • Poullis, C. and You, S., 2010. Delineation and geometric modeling of road networks. ISPRS J. Photogramm. 65(2), 2010 pp.165-181.
  • Asef Zare, Mostafa, OkautiAutomatic road extraction based on neuro-fuzzy algorithm, Proceeding, ROCOM'10 Proceedings of the 10th WSEAS international conference on Robotics, control and manufacturing technologyWorld Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA ©2010
  • Rajeshwari, M ,Senthilnath, J.; .; Omkar, S. N.Semi Automatic Road Extraction using high resolution satellite imagery in urban areas, Indian Engineering Congress 2007, Uadipur ,Rajasthan, 14-15 December, 2007
  • S. N. Omkar, Senthilnath J and M. Rajeswari, “A Variational Level Set method for road extraction in satellite images”, in the Proceedings of the Conference on Advances in Space Science and Technology, CASST’S 2008, , IIT Kharagpur. January 14-16, 2008
  • Trish Keaton and Jeffrey Brokish (2002). A level set method for the extraction of roads from Multispectral Imagery, Proceedings of the 31st Applied Imagery Pattern Recognition Workshop (AIPR.02) 0-7695-1863-X/02 $17.00 © 2002 IEEE
  • X. Cai, A. Sowmya and J. Trinder (2006), Machine Learning Approach for Automatic Road Extraction, Proceedings of the ASPRS 2006 Annual Conference, Reno, Nevada, USA, May 1-5, 2006.
  • M. Ravanbakhsh, C. Heipke, K. Pakzad ,Extraction of Road Junction Islands from High Resolution Aerial Imagery Using Level Sets , The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3a. Beijing 2008
  • Bibo Lu, Yongxia Ku, Hui Wang, "Automatic Road Extraction Method Based on Level Set and Shape Analysis," icicta, vol. 3, pp.511-514, 2009 Second International Conference on Intelligent Computation Technology and Automation, 2009
  • Qihui Zhu, Mordohai, P.; , "A minimum cover approach for extracting the road network from airborne LIDAR data," Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on , vol., no., pp.1582-1589, Sept. 27 2009-Oct. 4 2009
  • A.Grote , M. Butenuth, C. Heipke,Road Extraction in Suburban Areas Based on Normalized Cuts PIA07 - Photogrammetric Image Analysis --- Munich, Germany, September 19-21, 2007
  • Anne Grote, Franz Rottensteiner,Automatic Road Network Extraction in Suburban Areas from Highresolution Aerial Images: Paparoditis N., Pierrot-Deseilligny M., Mallet C., Tournaire O. (Eds), IAPRS, Vol. XXXVIII, Part 3A – Saint-Mandé, France, September 1-3, 2010
  • Luminita A.Vese and Tony F.Chan,( 2001) A multiphase level set framework for image segmentation using the Mumford and Shah model, UCLA CAM Report ,( 2001) 01-25
  • Chunming Li , Chenyang Xu , Changfeng Gui , and Martin D. Fox (2005), Level Set Evolution Without Re-initialization: A New Variational Formulation Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05) 2005
  • Shi, J. and Malik J. (2000) Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(8): 2000 888-905.
  • Wiedemann. C, Heipke. C, Mayer. H and Jamet. O (1998). Empirical evaluation of automatically extracted road axes. Empirical Evaluation Methods in Computer Vision. IEEE Computer Society Press. 1998 pp. 172–187.
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Level set median filtering Normalized cuts Performance Evaluation Urban Road extraction

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