[BKYST] Application of Image Processing for Quality Control in V-bending Processing

Abstract

The V-bending process, widely used across various everyday products, has experienced a growing demand for tighter quality control measures. Traditional methods often rely on visual inspection or manual angle gauges, which can be time-consuming and prone to human error. This journal explores the application of image processing techniques for automated angle measurement of V-bending workpieces. The proposed method places a camera to capture an image of the workpiece. Subsequently, the Canny edge detection algorithm is employed to identify the edges within the image. These edges are then utilized by the Hough transform, a technique capable of extracting lines from the detected edges. Through analysis of the extracted lines, the angle of the V-bending is calculated. This approach offers a promising alternative to traditional quality control methods, potentially leading to increased accuracy and efficiency. While the result shows high reliability with a minimal error, further development can focus on refining the system's factors like camera placement and specimen variations. Ultimately, this method paves the way for a more automated and reliable approach to V-bending quality control besides existing high-precision techniques like Coordinate Measuring Machines (CMM).