Real-time image defect detection system of cloth digital printing machine

Abstract

Abstract In order to solve the surface defects such as white silk, spots and wrinkles in the process of digital printing, a surface defect detection system for printed fabrics based on accelerated robust feature algorithm was proposed. Image registration is mainly carried out through accelerated robust feature (SURF); bidirectional unique matching method is adopted to reduce mismatch points, achieve accurate image registration, and extract defect information through differential algorithm. The performance of the improved surfing algorithm is verified by using multiple images. The experimental results show that compared with the traditional template matching method, the detection accuracy of the system detection algorithm is 12% higher, and the average time is 42.81 ms shorter than the traditional template matching method. Experiments show that the improved surfing algorithm has short time and high precision. The system can meet the actual production needs. The new system can detect surface defects on printed fabrics with an accuracy of 98%. Conclusion: The algorithm has higher detection rate and faster detection speed, which can meet the needs of practical industrial applications.