Automatic Bridge Extraction for Optical Images

This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge, we extract the river regions which the bridges are included in. Firstly, we segment the optical image to get the coarse water bodies using iterative threshold, eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then, the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally, the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle.