<title>Design of binary rotation-invariant filters with genetic algorithm</title>

Abstract

A rotation invariant binary circular filter has been developed for optical pattern recognition. The filter is generated using an iterative numerical optimization method. The optimization is based on the genetic algorithm, which fits very well in optical systems due to its parallel nature. The features of the genetic algorithm provide a highly efficient and rapid learning process. During training, the parameters of a binary circular filter are selected to maximize the distinction between the target and other expected objects in the image. The genetic algorithm is searching through the complete filter space for the global solution, this is the filter with the best performance. These iteratively designed filters are good discriminators because they utilize all the spatial visual information about the target. The design of the rotation invariant filter does not require any a priori information about the target image. The rotation invariant filters are designed as binary circular filters to be suitable for real- time applications, when combined with spatial light modulators.