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.
曹国，杨新. 基于水平集方法的航拍图片人工区域的分割检测[J]. 模式识别与人工智能, 2006, 19(4): 526-530.
CAO Guo, YANG Xin. ManMade Objects Detection from Aerial Images Based on Level Set Method. , 2006, 19(4): 526-530.
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2006, Vol. 19 
