Online Detect System Study And Design For Cord Fabric Defect Based On Matrox Image Procesing Board

This study aims to build an online cord fabric's defect detection hardware platform based on image processing board, and explore real time defect detection methods with high accuracy. The challenge of acquiring high quality images in this kind of system comes from the large width of the cord fabric and the movement velocity which is high and varies in a large extent. The hardware platform is subdivided into three parts: first, the optical imaging subsystem including the line camera, lens and lamp-house; second, motion synchronization subsystem composed of an encoder and the frequency division controller, in which accurate speed measurement of the cord fabric is implemented in order to synchronize the acquisition frequency of the line camera; third, the image acquisition subsystem composed of image processing board and PC. In this paper, hardware is elaborately selected and their parameters are calculated subsequently. Implementation of the motion synchronization subsystem, both hardware and software, is conducted. By aid of the MIL library, an image acquisition program is realized in Visual Studio. The whole image acquisition system has been installed and adjusted in the field. Experiments approve that our system can obtain images with high quality stably in practice.For quickly judging whether the cord fabric has defects, methods based on histogram and two thresholds in grayscale are compared. Of which based on the histogram detection method is a more basic way, because of its own shortcomings, in the false detection rate is not yet meet the requirements of the system. According to the structural characteristics of texture cord fabric, the method based on grayscale double thresholds selects a large number of maximum grayscale values and minimum grayscale values in normal image as this method's double thresholds, and then comparing with regional and longitudinal, to judge whether there is abnormity in grayscale. Under the constraints between maximum values and minimum values, it can accurately detect defects quickly, so it is more suitable for quick judgment.