A New Building Mask Using the Gradient of Heights for Automatic Building Extraction
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A number of building detection methods have been proposed in the literature. However, they are not effective in detecting small buildings (typically, 50 m2) and buildings with transparent roof due to the way area thresholds and ground points are used. This paper proposes a new building mask to overcome these limitations and enables detection of buildings not only with transparent roof materials but also which are small in size. The proposed building detection method transforms the non-ground height information into an intensity image and then analyses the gradient information in the image. It uses a small area threshold of 1 m2 and, thereby, is able to detect small buildings such as garden sheds. The use of non-ground points allows analyses of the gradient on all types of roof materials and, thus, the method is also able to detect buildings with transparent roofs. Our experimental results show that the proposed method can successfully extract buildings even when their roofs are small and/or transparent, thereby, achieving relatively higher average completeness and quality.
2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
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Pattern Recognition and Data Mining