Segmentation of Cross - Sectional Images Using Fuzzy Logic
نویسنده
چکیده
In this paper, we present a new segmentation method for range images consisting of a set of planar cross-sectional contours. Our approach is novel in that it uses fuzzy criteria for grouping primitives and identifying homogeneous regions. We have tried our method with images provided by a structured light sensor. In this case, the image sequence corresponds to the scene profiles obtained with the successive positions of a rotating plane of laser light. We assume that the object surfaces can be modelled by a set of quadratic patches. The primitives used for region segmentation result from the approximation of the light profile by second order curves. An efficient tracking of these noisy curves is achieved by using a fuzzy decision-making algorithm. Region growing is then performed by our method by matching 2D curves from the image sequence. We present results obtained with real scenes consisting of multiple objects of arbitrary shapes. They show that an efficient surface segmentation may be obtained with fewconstrained environments including planar or curved shapes.
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