Development of Defect Classification Algorithm for POSCO Rolling Strip Surface Inspection System

Surface inspection system (SIS) is an integrated hardware-software system which automatically inspects the surface of the steel strip. It is equipped with several cameras and illumination over and under the steel strip roll and automatically detects and classifies defects on the surface. The performance of the inspection algorithm plays an important role in not only quality assurance of the rolled steel product, but also improvement of the strip production process control. Current implementation of POSCO SIS has good ability to detect defects, however, classification performance is not satisfactory. In this paper, we introduce POSCO SIS and suggest a new defect classification algorithm which is based on support vector machine technique. The suggested classification algorithm shows good classification ability and generalization performance