The quality of product of manufacturing industries depends on dimension accurately and surface roughness quality. There are many types of surface defects and levels of surface roughness quality. Ironing process is one type of metal forming process, which aims to reduce the wall thickness of the cup-shaped or pipes products, thus increasing the height of the wall. Manually surface inspection procedures are very inadequate to ensure the surface in guaranteed quality. To ensure strict requirements of customers, the surface defect inspection based on image processing techniques has been found to be very effective and popular over the last two decades. The paper has been reviewed some papers based on image processing for defect detection. It has been tried to find some alternatives of useful methods for product surface defect detection of ironing process.
Research on Surface Defect Detection of Aluminum based on Image Processing
