Abstract
Pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller compared to that of the latter. In this paper we propose a new classifier that exploits this property, yielding a low complexity yet effective target detection algorithm. This algorithm, called the maximal rejection classifier (MRC), is based on linear successive rejection operations. An application of detecting faces in images is demonstrated using the MRC with encouraging results.
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