This paper deals with a novel method of pattern recognition, in which recognition is effected by sequential sweeping along preferred directions. The chosen set of measurement directions (x1,x2, …xn) are first ordered according to preference and then the axes are swept sequentially in that order. An algorithm is proposed which gives a code representation for the pattern clusters in ann-dimensional pattern space. Two models are proposed for the recognizer. It is shown that the method is capable of 100% recognition of learning patterns, under the assumption that no two patterns belonging to different categories occupy the same pattern point in the pattern space.