Laser-Enhanced Machine Vision for Edge Profile Measurement of Thin Film Printed Electronics

Thin film printed electronics, such as flexible circuits and sensor sheets, require non-contact inspection to detect defects and edge degradation. The present paper presents a laser-enhanced machine vision framework for detecting and analyzing the edges of printed conductive tracks using Canny edge detection and Otsu thresholding. Using a coherent laser source, Otsu's method enhances contrast at the ink-substrate interface, enabling robust segmentation of edge lines. Canny operator is applied to thresholded images to extract precise edge profiles. Multiple printed tracks are analyzed to calculate four lateral edge roughness values (Ra). As a result, the values are 40.43 µm, 40.09 µm, 50.26 µm and 40.94 µm. The results show that the suggested method can detect and qualify variations in edge parameters. Printed electronics are produced using an inline inspection and quality control system based on non-contact, high-resolution, and scalable technologies.