Document Type : علمی - پژوهشی


1 PhD student of Remote Sensing, Geomatics Engineering Faculty, K. N. Toosi University of Technology

2 Associated Professor, Geomatics Engineering Faculty, K. N. Toosi University of Technology

3 Associated Professor of Remote Sensing Research Center Faculty of Geodesy and Geomatics Engineering K. N. Toosi University of Technology


Nowadays, extraction of roads from digital aerial and satellite images is a common method of road database construction. Regarding to massive amount of road data and time and cost effective updating requirements, automation procedure is becoming an essential. In this research, which is mostly concentrated on road vectorization process, an automatic approach of road centerline vectorization from detected road image with negligible operator interventions is designed.  The proposed system consists of two main stages including road key points determination and connection. At the first stage, the road key points representative of the road centerline are determined using particle swarm optimization clustering. At the second stage, in order to model the road networks weighted graph theory is considered. In this model cost of each connection is calculated by aggregating appropriate road geometric criteria by means of ordered weighted averaging operators. The least cost connections constitute the vectorized road networks. The proposed approach was implemented on several high resolution satellite images and their results were compared with the results of the minimum spanning tree algorithm. On the whole, the obtaining results proved the efficiency of the vectorization approach in attaining the complete and accurate road network. Extracting different road shapes including direct and curved roads, roads with different widths, parallel roads with different distances, junctions and square with average RMSE value about 0.9 meter, average completeness of %94, and average correctness greater than %95 proves the efficiency of the algorithm in yielding complete road networks. 


  1. خصالی الف، ولدان زوج، م.ج.، دهقانی، م.، مختارزاده، م.، 1392، مقایسة استخراج عارضۀ راه در مناطق شهری از تصاویر با حد تفکیک بالای TerraSAR-X و آیکونوس با استفاده از اطلاعات بافت در الگوریتم‌های شبکۀ عصبی، سنجش از دور و GIS ایران، سال پنجم، شماره چهارم.
  2. عامری، ف.، ولدان زوج، م.ج.، مختارزاده، م.، مبارکی، ع.م.، 1390، استخراج اشکال متفاوت راه از تصاویر ماهواره‌ای با قدرت تفکیک‌های مختلف مکانی، سنجش از دور و GIS ایران، سال سوم، شماره چهارم، صص. 18-1 .
  3. محمدزاده، ع.، 1388، استخراج اتوماتیک راه‌های اصلی از تصاویر ماهواره‌ای رنگی بزرگ‌مقیاس با استفاده از منطق فازی و توابع مورفولوژی، پایان نامه دکتری، دانشگاه صنعتی خواجه نصیرالدین طوسی.
  4. Clode, S., Rottensteiner, F., Kootsookos, P. & Zelniker, E., 2007, Detection and Vectorization of Roads from Lidar Data, Photogrammetric Engineering & Remote Sensing 73(5), 517-536.
  5. Cornelis, C., Verbiest, N. & Jensen, J., 2010, Ordered Weighted Average Based Fuzzy Rough Sets, Proceedings of the 5th International Conference on Rough Sets and Knowledge Technology (RSKT 2010), p. 78 – 85.
  6. Doucette, P., Agouris, P., Stefanidis, A. & Musavi, M., 2001, Self-Organised Clustering for Road Extraction in Classified Imagery, ISPRS Journal of Photogrammetry and Remote Sensing (55), 347-358.
  7. Ferchichi, S. & Wang, S., 2005, Optimization of Cluster Coverage for Road Center-Line Extraction in High Resolution Satellite Images, Proceedings of the IEEE International Conference on Image Processing, pp. 201–204
  8. Jelokhani-Niaraki, M. & Malczewski, J., 2014, A Group Multicriteria Spatial Decision Support System for Parking Site Selection Problem: A Case Study, Land Use Policy, (42) 492–508.
  9. Kennedy, J., & Eberhart, R.C., 1997, A Discrete Binary Version of The Particle Swarm Algorithm, In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pages 4104-4108, IEEE Press, Piscataway, NJ, 1997.
  10. Omran, M.G., Engelbrecht, A.P. & Salman, A., 2006, A Dynamic Clustering Using Particle Swarm Optimization with Application in Image Classification, Pattern Analysis and Application. 332-344.
  11. Malczewski, J., 1999, GIS and Multicriteria Decision Analysis, Wiley, New York.
  12. Mena, J.B., 2002, Vectorizacion Automatica de una Imagen Binaria Mediante K-Means Degeneracion de la Triangulacion de Delaunay, Revista de la Asociacion Española de Teledeteccion 17, 21-29.
  13. Mena, J.B., 2006, Automatic Vectorization of Segmented Road Networks by Geometrical and Topological Analysis of High Resolution Binary Images, Knowledge-Based Systems 19, 704–718.
  14. Mohammadzadeh, A., Tavakoli, A. & ValadanZoej, M.J., 2006, Road Extraction Based on Fuzzy Logic and Mathematical Morphology from Pan-Sharpened Ikonos Images, Photogrammetric Record, 21(113): 44-60.
  15. Mokhtarzade, M., ValadanZoej, M.J., Ebadi, H. & Sahebi, M.R., 2010, An Innovative Image Pace Clustering Technique for Automatic Road Network Vectorization, Photogrammetric Engineering & Remote Sensing, Vol. 76, No. 7, pp. 841–852.
  16. Shanmugam, L. & Kaliaperumal, V., 2015, Water Flow Based Geometric Active Deformable Model for Road Network, ISPRS Journal of Photogrammetry and Remote Sensing, (102) 140–147.
  17. Stillwell, W.G., Seaver, D.A. & Edwards, W., 1981, A Comparison of Weight Approximation Techniques in Multi-Attribute Utility Decision Making, Organ. Behav. Hum.Perform. 28 (1): 62–77.
  18. Wiedemann, C., 2003, External Evaluation of Road Networks, ISPRS Archives, Vol. XXXIV, Part 3/W8, Munich, 17.-19.
  19. Yager, R.R., 1988, On Ordered Weighted Averaging Aggregation Operators in Multicriteria Decision making, IEEE Trans. Syst. Man Cybern. Syst. Hum. 18 (1), 183–190.
  20. Yager, R.R., 1997, On the Inclusion of Importances in OWA Aggregations, In: Yager, R.R., J. Kacprzyk, (Eds.), The Ordered Weighted Averaging Operators, Kluwer Academic Publishers, Boston, pp. 41–59.