Improved the Notched Character Defect Detection Algorithm of YOLOv8
Engraved character marking technology is a method of creating permanent identifiers on workpiece surfaces by directly removing material or causing plastic deformation through physical action. This technology is widely used in industrial fields for product traceability, quality control, and anti-counterfeiting certification. However, long-term operation of marking equipment leading to aging and fluctuations in process parameters can easily cause character defects such as broken strokes and distortions, directly affecting the readability and reliability of the identification. This paper addresses the issue of low detection accuracy for common character defects in the original YOLOv8 model by optimizing it. Experiments show that the optimized model significantly improves detection accuracy for various defect types compared to the original model, achieving satisfactory detection performance.
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