Computer Vision System for Manufacturing of Micro Workpieces

Two neural network based vision subsystems for image recognition in micromechanics were developed. One Subsystem is for shape recognition and another subsystem is for texture recognition. Information about shape and texture of the micro workpiece can be used to improve precision of both assembly and manufacturing processes. The proposed subsystems were tested off-line in two tasks. In the task of 3mm screw shape recognition the recognition rate of 92.5% was obtained for image database of screws manufactured with different positions of the cutters. In the task of texture recognition of mechanically treated metal surfaces the recognition rate of 99.8% was obtained for image database Of four texture types corresponding to metal Surfaces after milling, polishing with sandpaper, turning with lathe and polishing with file. We propose to combine these two subsystems to computer vision system for manufacturing of micro workpieces.