Abstract A novel method for detecting manmade objects in aerial images is described. The method is based on a simplified MumfordShah model. It applies fractal error metric and additional constrainttexture edge descriptor on the image to get a preferable segmentation. Manmade objects and natural areas are optimally differentiated by evolving the partial differential equation for MumfordShah model. The method avoids selecting a threshold, which, if improperly selected, often results in great segmentation errors to separate the fractal error image. Experiments of the segmentation show that the proposed method is efficient.
[1] Mayer H. AutomaticObject Extraction from Aerial Imagery—A Survey Focusing on Buildings. Computer Vision and Image Understanding, 1999, 74(2): 138-149
[2] Li J, Najmi A, Gray R M. Image Classification by a Two-Dimensional Hidden Markov Model. IEEE Trans on Signal Processing, 2000, 48(2): 517-533 [3] Reno A L, Booth D M. Using Models to Recognise Man-Made Objects. In: Proc of the 2nd IEEE Workshop on Visual Surveillance. Fort Collins, USA, 1999, 33-40 [4] Solka J L, Marchette D J, Wallet B C. Identification of Man-Made Regions in Unmanned Aerial Vehicle Imagery and Videos. IEEE Trans on Pattern Analysis and Machine Intelligence, 1998, 20(8): 852-857 [5] Smyrniotis C, Dutta K. A Knowledge-Based System for Recognizing Man-Made Objects in Aerial Images. In: Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Ann Arbor, USA, 1988, 111-117 [6] Carlotto M J. Detecting Man-Made Features in SAR Imagery. In: Proc of the International Symposium on Geoscience and Remote Sensing. Lincoln, USA, 1996, Ⅰ: 34-36 [7] Levitt S, Aghdasi F. Texture Measures for Building Recognition in Aerial Photographs. In: Proc of the South African Symposium on Communications and Signal Processing. Grahamstown, South African, 1997, 75-80 [8] Cooper B E, Chenoweth D L, Selvage J E. Fractal Error for Detecting Man-Made Features in Aerial Images. Electronics Letters, 1994, 30(7): 554-555 [9] Haala N, Brenner C. Interpretation of Urban Surface Models Using 2D Building Information. Computer Vision and Image Understanding, 1998, 72(2): 204-214 [10] Randen T, Husoy J H. Filtering for Texture Classification: A Comparative Study. IEEE Trans on Pattern Recognition and Machine Intelligence, 1999, 21(4): 291-310 [11] Chan T F, Vese L A. Active Contours without Edges. IEEE Trans on Image Processing, 2001, 10(2): 266-277 [12] Sethian J A. Level Set Methods and Fast Marching Methods Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. 2nd Edition. Cambridge, UK: Cambridge University Press, 1999 [13] Yang X. The Principles and Applications of Partial Differential Equations in Image Processing. Shanghai, China: Shanghai Jiaotong University Press, 2003 (in Chinese) (杨 新. 图像偏微分方程的原理与应用.上海:上海交通大学出版社, 2003) [14] Castleman K R. Digital Image Processing. Opper Saddle River, USA: Prentice Hall, 1979 (Castleman K R, 著;朱志刚,等,译.数字图像处理.北京:电子工业出版社, 1998)
2006, Vol. 19 
