08-08-2023 дата публикации
Номер: CN116563276A
Принадлежит:
The invention discloses a chemical fiber filament online defect detection method and detection system, and belongs to the technical field of image processing, and the method comprises the following steps: S1, constructing a machine learning model; s101, collecting defect images of the chemical fiber filaments; s102, training defect images: firstly, carrying out feature solution on the collected defect images one by one to obtain A gray features and B shape features, and then forming feature vectors by the A gray features and the B shape features of each defect image; finally, the feature vector serves as an input layer of a machine learning model, the defect category serves as an output layer result, and the machine learning model is trained; s2, acquiring an image to be detected; s3, carrying out image calibration; s4, defect detection; firstly, a to-be-detected image is subjected to image preprocessing; and importing an image preprocessing result into a machine learning model to obtain ...
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