Architecture for binary mathematical morphology reconfigurable by genetic programming

Abstract

Mathematical morphology supplies powerful tools for low level image analysis, with applications in robotic vision, visual inspection, medicine, texture analysis and many other areas. Many of the mentioned applications require dedicated hardware for real time execution. In this paper, the development of a novel reconfigurable hardware using logical and morphological instructions generated automatically by a linear approach based on genetic programming is proposed. The hardware is capable of processing binary images at high speed. The developed system is based on high-capacity PLDs and has among the possible applications: automatic construction of image filters, intelligent pattern recognition, to name just a few. Some applications using the developed reconfigurable system are presented and the results are discussed and compared with other approaches.