Issue No. 02 - February (1998 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.659940
<p><b>Abstract</b>—We propose a novel image segmentation technique using the robust, adaptive least <it>k</it>th order squares (ALKS) estimator which minimizes the <it>k</it>th order statistics of the squared of residuals. The optimal value of <it>k</it> 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.</p>
Robust methods, least kth order squares, range image segmentation, surface fitting, autonomous image analysis.
R. Park, K. Lee and P. Meer, "Robust Adaptive Segmentation of Range Images," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 200-205, 1998.