Limited Receptive Area neural classifier for texture recognition of metal surfaces

Abstract

Abstract. The Limited Receptive Area (LIRA) neural classifier is proposed for texture recognition of mechanically treated metal surfaces. It can be used in systems that have to recognize position and orientation of complex work pieces in the task of assembly of micromechanical devices. The performance of the proposed classifier was tested on specially created image database in recognition of four texture types that correspond to metal surfaces after: milling, polishing with sandpaper, turning with lathe and polishing with file. The promising recognition rate of 99.7% was obtained.