Area Based Diameter Measurement Algorithm for Industrial Machine Vision Applications

Abstract

Measurements of serial production workpieces in the industry are performed by camera-controlled systems thanks to the advantage of speed. The measurement success of camera systems largely depends on the measurement algorithm. In this paper, an area-based diameter measurement algorithm that can be used in industrial machine vision applications is proposed. The success of the proposed method is demonstrated based on the sub-computation metric. In the proposed method, firstly, the noise on the obtained image is cleaned according to the connected component analysis. Then, the inner and outer diameters of the largest component are determined according to the area calculation. In the designed experimental setup, a back lighting illumination has been preferred. According to 3 different positioning types in the field of view of the camera, a total of 40 stamps of 4 types were measured 20 times with 3 different lenses. According to the test results, it has been observed that the position of the part on the field of view greatly affects the repeatability measurements. Also, sub-computation metric (C) is measured 2 in random positioning. This value increases up to 5 in the limited positioning that meets the industrial conditions. Tests have shown that the proposed method can measure the diameters of workpieces with precise tolerances in an industrial setting.