Key Image Processing Technology In Optical Defect Inspection Of FPC

Flexible Printed Circuit, FPC, is the only way to interconnect the electronic device to achieve miniaturization. With the widespread use of mobile devices, FPC is facing an increasingly broad market. However, the quality control in FPC production process still need to rely on manual testing, which is inefficient and difficult to ensure testing quality. With the improvement of production efficiency and quality requirements from customer, using imaging technology to test FPC production quality must become a must to improve production by the choice. This paper is focused on several key image processing technology in FPC optical defect detection. It is going to discuss the structure of the system and some image processing algorithms, etc, based on the FPC characteristics like.Any image testing applications need to design its mechanical structure, software program and algorithm program according to production characteristics of the detected object. Therefore, this paper will introduce the characteristic about two modes of FPC production as well as the characteristics of respective optical detection system. According to these characteristics, this paper will discuss reasonable structure of image testing system, and then design appropriate mechanisms for image processing and software on this basis.In order to improve detection accuracy, FPC optical detection applications requires the use of multiple cameras to capture images of a whole FPC in each local area, or a camera in the lead of motion platform to capture them. These images are then stitched into a complete picture to compare with the reference image. One focus of this paper is to discuss methods about feature detection, extracting feature descriptor extraction, matching feature matching and fusion splicing in the process of stitching FPC image. Whether image stitching or comparison, the algorithm principle is based on the relevant ideal camera model and ideal posture, however, there is often a distortion of the actual camera, engineering installation is also difficult to avoid deviations from the ideal situation, so this paper will discuss the nonlinear distortion in image caused by the lens and the geometric distortion caused by camera posture, as well as the relevant correction methods.Edge Information has important applied value in FPC optical detection. In some special applications, such as using microscopic imaging or X-ray imaging to observe FPC, very much interference is present in the original image,which led to the traditional edge detection methods can’t simultaneously effectively suppress interference and maintain the edge positional accuracy. The most prominent achievements of this paper is a new edge detection method, its principle is to use the evolution law of image edge in scale space to detect and select image edges. The algorithm ensures the accuracy of the edge position as well as suppresses interference information.This paper also discusses some detection methods for several common defects in FPC production process. For short-circuit, over copper, circuit, and small gap defects, this article design a detection method that first search the preliminary position of the defect with the help edge density information and then fine match to confirm the defect. This paper also discusses the use of thinning algorithm on line width detection.