Feature extraction using pulse coupled neural network and shape information

Feature extraction of specified object is an important preprocessing stage in machine vision systems. In this paper we present a novel hybrid feature extraction method using PCNN (Pulse Coupled Neural Network) and shape information. First, we use PCNN firing map train to formulate object time signature, then we use roundness of each firing map to formulate object shape information vector the final feature matrix we got is combined lime signature and roundness. We take correlations as our judge criteria in our experiments. It has been proved that the algorithm is not sensitivity with the rotation, scaling and translation of the object and is a useful method for target recognition applications.