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Robust Adaptive Segmentation of Range Images
February 1998 (vol. 20 no. 2)
pp. 200-205

Abstract—We propose a novel image segmentation technique using the robust, adaptive least kth order squares (ALKS) estimator which minimizes the kth order statistics of the squared of residuals. The optimal value of k is determined from the data, and the procedure detects the homogeneous surface patch representing the relative majority of the pixels. The ALKS shows a better tolerance to structured outliers than other recently proposed similar techniques: Minimize the Probability of Randomness (MINPRAN) and Residual Consensus (RESC). The performance of the new, fully autonomous, range image segmentation algorithm is compared to several other methods.

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Index Terms:
Robust methods, least kth order squares, range image segmentation, surface fitting, autonomous image analysis.
Kil-Moo Lee, Peter Meer, Rae-Hong Park, "Robust Adaptive Segmentation of Range Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 2, pp. 200-205, Feb. 1998, doi:10.1109/34.659940
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