A Method for Automated Control of Electronic Components on Microfocus X-ray Images

Abstract

Introduction. Machine vision systems are increasingly used in industrial production, particularly for monitoring the quality of electronic components. Radiographic (Х-ray) inspection is currently one of the most popular types of non-destructive testing. Electronic components are typically characterized by a small size, hence, their radiographic inspection should be based on obtaining images and their further enlargement. X-ray equipment for performing such studies is designed such that there are relatively small input doses of X-ray radiation in the plane of the receiver, which leads to a higher image noise than that using conventional X-ray devices.Aim. To develop a method for automated object recognition on microfocus X-ray images.Materials and methods. A method for segmentation of X-ray images is proposed. In the first step, adaptive median filtering is performed followed by correction of the image background by subtracting the distorting function. Next, the contours of the objects in the image are identified using the Canny edge detector followed by recognition of the objects on the resulting image.Results. The developed method was tested for quality control of the installation of microcircuits and for determining the number of electronic components. The experiments confirmed the accuracy of the proposed method. When monitoring the quality of microcircuit installation, the number of detected defects differed from that verified by the operator by less than 10 %. The average error of the proposed method was less than 0.1% when determining the number of electronic components.Conclusion. The proposed method for object recognition on microfocus X-ray images demonstrated sufficient accuracy in typical tasks of non-destructive testing of electronic components.