Detection of road signs by using a multiple correlator and partial invariant filters

Abstract

Study of pattern recognition technique using optical correlation has a long history. However, the technique has not been put to practical use yet. The main reason is that the amount of information included in temporally and spatially changeable images from the real world is too large to be processed by a single optical correlator. Another reason was a lackoffunctional optical or optoelectronic devices, such as spatial light modulators, micro lens arrays and smart pixel devices. However, functional optical devices have been developed andbecome available in optical systems. Nowadays it becomes possible to realize an optical computing system surpassing electronic system in processing speed, by applying the speed and parallelism of light. We think it is possible to realize a machine vision system which shows an adequate ability ofpattern recognition au! processing speed by a multiple optical correlator' using a set of optimized correlation filters and functional optoelectronic devices. In this paper, we designedsets ofoptical correlation filters fordetection andclassification of road signs in a image of real world scene, in order to evaluate the ability of machine vision system using multiple optical correlator. The correlation filter set is designedas to have partial invariance fordistortion to adaptto the change of aspect of road signs. Computer simulation result shows that the combination of multiple optical correlator and partial invariant correlation filter can indicate high performance of pattern recognition.