EXTRACTION AND REGISTRATION OF REAL WORLD SCENES

In this paper we present an efficient edge detection algorithm for the extraction of linear features in both range and intensity image data. The purpose is to simplify the dense datasets and to provide stable features of interest, which are used to recover the positions of the 2D cameras with respect to the geometric model for tasks such as texture mapping. In our algorithm the required features of interest are extracted by an analysis of the mean curvature values. This additionally allows the discrimination of different edge types like crease or step edges. As it will be demonstrated, the algorithm features computational efficiency, high accuracy in the localization of the edge points, easy implementation, and robustness against noise. The algorithm was initially developed for range image segmentation and has been extended to segment intensity images with some modifications. The generality and robustness of the algorithm is illustrated during processing of complex cultural heritage scenes. ∗ Corresponding author

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