Abstract
A scale and rotation invariant pattern recognition system using complex-log mapping (CLM) and an augmented second order neural network (SONN) is proposed. CLM is very useful for extracting the scale and rotation invariant features. The results are, however, given in a wrap-around translated form. This problem is solved with an augmented SONN. Experimental results show that the proposed system has improved recognition performance.
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