Multi-level image processing and deep learning model collaborative battery defect detection method

The invention provides a multi-level image processing and deep learning model collaborative battery defect detection method, and belongs to the technical field of battery manufacturing and industrial detection. The method comprises the following steps: preprocessing an initial battery image through a traditional image processing algorithm; cutting the image by using the detected circular contour, and removing a defect sample with relatively large deformation; a preprocessed battery image is transmitted into a deep learning model, and the model carries out defect detection deeply by using an advanced feature extraction capability. The collaborative method not only helps to eliminate unnecessary interference, but also improves the accuracy and efficiency of detection, has stronger adaptability and real-time performance in the aspect of battery quality control, provides an efficient and reliable quality control means for the battery manufacturing industry, and promotes the continuous development of the battery m