Automatic Detection of Buildings from Aerial Images Using Color Invariant Features and Canny Edge Detection

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-11 Number-8
Year of Publication : 2014
Authors : Shraddha Singhal , Sudha Radhika


Shraddha Singhal , Sudha Radhika. "Automatic Detection of Buildings from Aerial Images Using Color Invariant Features and Canny Edge Detection", International Journal of Engineering Trends and Technology (IJETT), V11(8),393-396 May 2014. ISSN:2231-5381. published by seventh sense research group


Automatic detection of damaged buildings from aerial and satellite images is an important problem for rescue planners and military personnel. A method for detecting the buildings from high resolution color aerial images is proposed in this paper. The aim is to extract the buildings from high resolution color aerial images using color invariance property and canny edge detection technique. The buildings on the aerial images are 2-dimentional structures which are mostly made up of regions having borders being straight line which depicts edges in the images. The color information in the aerial image using a specific color index is extracted. The green area is separated by vegetation green from color aerial image. Then the primary colored roofs such as blue and red is segmented with the help of the primary color bands, such as red, green and blue bands. Once red, blue roof tops are segmented and separated from the imagery. Using canny edge detection method, the other colored roof tops are also segmented. Our proposed method is able to detect 85-90% buildings from color aerial images


[1] R. B. Irvin and D. M. McKeown,“Methods for exploiting the relationship between buildings and their shadows in aerial imagery ”IEEE Transactions on Systems, Man, and Cybernetics, vol. 19, no. 1, pp. 1564–1575, 1989
[2] Beril S?rmacek and Cem U¨ nsalan “Damaged Building Detection in Aerial Images using Shadow Information” Computer Vision Research Laboratory, Yeditepe University. 978-1-4244-2881-6/08,2008
[3] T. Kim and J.P. Muller., “Development of a graph-based approach for building detection” Image and Vision Computing, vol.7, pp.3-14, 1999.
[4] Sudha radhika, Yukio Tamura, Masahiro Matsui, “Automated detection of Tornado damage to building structures from Aerial imageries using color invariant features ” proceeding of 13TH international conference on Wind Engineering (ICWE13) Amsterdam, Netherlands July 2011 pp.10-15.
[5] T. Vu, M. Matsouka, and F. Yamazaki, “Shadow analysis in assisting damage detection due to earthquake from quickbird imagery,” Proceedings of the 10th international society for photogrammetry and remote sensing congress, pp. 607–611, 2004
[6] T. Guo, and Y. Yasuoka, "Snake-based approach for building extraction from high-resolution satellite images and height data in urban areas", Proceedings of 23rd Asian Conference on Remote Sensing, 2002.
[7] ] D. S. Lee, J. Shan, and J. S. Bethel, “Class-guided building extraction from ikonos imagery,", Geomatics Engineering, School of Civil Engineering, Purdue University, West Lafayette, IN 47907-1284, Photogrammetric Engineering & Remote Sensing, vol. 69, pp.143-150, February 2003.
[8] A. Huertas, R. Nevatia, and D. Landgrebe, “Use of hyperspectral data with intensity images for automatic building modeling," Sunnyvale, California, Proceedings of the Second International Conference on Information Fusion, July 1999.
[9] M. Roux and D. McKeown, “Feature Matching for Building Extraction from Multiple Views,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 46-53, June 1994.
[10] A. Huertas and R. Nevatia., “Detecting buildings in aerial images,” Computer Vision, Graphics and Image Processing, vol. 41, pp. 131–152, 1988.
[11] J. Canny., “A Computational Approach to Edge Detection,” IEEE Trans.Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, June 1986.
[12] N. Otsu., “A threshold selection method from gray-level histograms,”IEEE Trans on SMC, vol. 9, pp. 62–66, 1979.
[13] T. Gevers and A. W. M. Smeulders, “Pictoseek: Combining color and shape invariant features for image retrieval,” IEEE Transactions on Image Processing, vol.9, pp.102–119, 2000.
[14] C. ¨Unsalan and K. L. Boyer, “Linearized vegetation indices based on a formal statistical framework,” IEEE Trans on GeoRS, vol. 42, pp. 1575–1585, 2004.

Aerial Images, Building Detection, Canny Edge Detection, Color Based Segmentation, Color Index