Defective Product Detection Using Image Processing

Automation is very important factor in an industry which manufactures product in mass quantity. After manufacturing product, to make decision of rejecting or accepting is taken by measuring quality parameters. To measure quality parameters such as dimensions and features of manufactured product inspection is done manually in almost manufacturing industries. Manual assessment is time consuming, costly, sometimes inaccurate and manual assessment for complicated shapes is very difficult. To overcome these problems quality control and quality management for sensitive industrial product is feasible by use of image processing techniques. In this study use of 2D and 3D image processing is compared to detect edge defects. To extract features of manufactured product from image of product Principal Component Analysis (PCA) is used, defect detection in manufactured industrial products using edge detection methods gives the performance in acceptable range with them.