The definitions of the edge density and the segment complexity are given

and a novel algorithm for recognition of bridge without water under it in remote sensing image is proposed.Firstly

the edge is extracted with Canny operator

and the edge density for each pixel is calculated.The image is segmented base on the edge density.Secondly

the suspected bridge area is identified by a series of processing including using Hough transform to extract straight line and calculating segment complexity.Then texture features of the suspected bridge area are extracted to form a feature vector.Finally

each suspected bridge is classified by Back Propagation Neural Network(BPNN) based on this feature vector.The experimental results show that the algorithm can perform well to detect bridge targets.