Pairwise Permutation Coding Neural Classifier

In this paper we propose pairwise permutation coding neural classifier (Pairwise PCNC). This classifier develops the idea of the permutation coding neural classifier (PCNC), a multipurpose image recognition system based on random local descriptors (RLD). Previous tests of PCNC demonstrated good results in different image recognition tasks including: handwritten digit recognition, face recognition, and micro work piece shape recognition. Main advantage of the pairwise PCNC is its ability to deal with large displacements of the object in the image due to utilization of pairs of RLDs instead of individual RLDs. Pairwise PCNC was tested on the MNIST database and comparative results suggest the potential of the proposed approach.