Defect Straw Inspection Method Based on Machine Vision

The visual inspection of defect straw can overcome the shortcomings of manual inspection, such as low accuracy, low efficiency, and poor real-time performance. It plays an important role in improving the production capacity and automation level of the enterprise. This paper takes telescopic straws as the research object, divides the defect types into global defects and local defects by analyzing the characteristics of each defect, and elaborate on the detection process and detection algorithm involved for each defect. A detection method from global to local is proposed by using image processing technology. In addition, this paper also proposes a new corner detection method, which has strong robustness to target corner detection in noisy images after experimental comparison. Finally, after experimental verification, the defect detection rate of the detection method proposed in this paper reached 98.8%.