The Technique For Automatic Building Recognition And Mapping In Remote Sensing Images

Automatic Target Recognition (ATR) is a core technology in the field of remote sensing image processing. Recent commercial satellites, like IKONOS and QuickBird, provide a large quantity of high resolution remote sensing images. The ATR technology has become more useful and important. The goal of ATR in remote sensing images is to recognize the regions of interest, such as forests, lakes, crops, and buildings. In order to achieve this goal, multiple techniques like image processing, image feature extraction, image segmentation are used. After a target is recognized, a mapping procedure is needed to acquire the regular outline of this target. Automatic target recognition and mapping techniques are widely used in environment monitoring, military detective, agricultural estimation, and disaster control. They will be the key techniques of future GIS, digital globe, digital city system.The researches of this paper focus on automatic building recognition and mapping techniques in urban remote sensing images. By concluding and summarizing former methods, this paper proposes an application framework for automatic building recognition and mapping. There are three steps in this framework: candidate building area searching, building target verification, and building mapping. In the candidate building area searching step, an image segmentation method based on grey level co-occurrence matrix (GLCM) is adopted to get candidate building areas in an urban image.In the building target verification step, a method based on the dominant line segment is proposed. The dominant line segment (the longest line segment) of every candidate area is extracted by a procedure using region growing, edge detection, and Hough transform. Then, the real buildings are verified by judging the length of their dominant line segments.