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6 October 1998 Scene segmentation from vector-valued images using anisotropic diffusion
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Abstract
Scene segmentation is a pre-processing step for many vision systems. We are concerned with segmentation as a precursor to 3D scene modeling. Segmentation of a scene for this purpose usually involves dividing an image into areas that are relatively uniform in some value (e.g. intensity, range, or curvature). This single segmented image represents the analogous segmented scene. This paper presents a segmentation method that uses features to indicate boundaries or edges between regions. We incorporate features from multiple images types to obtain an more accurate segmentation of objects or object parts in the scene. Multiple features are not only combined directly to improve segmentation results, but they are also used to guide a smoothing operation. This smoothing technique preserves features representing edges while smoothing noise in the images.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel Grady Burgiss Jr., Eric D. Lester, Ross T. Whitaker, and Mongi A. Abidi "Scene segmentation from vector-valued images using anisotropic diffusion", Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); https://doi.org/10.1117/12.325797
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