Abstract: A method for training a surface defect detection model as well as a method and a system for detecting a surface defect are provided. The method and the system for detecting a surface defect adopt the trained surface defect detection model. The method for training a surface defect detection model includes acquiring a normal image of a product and an external image that is irrelevant to the product and inputting the normal image and the external image into a deep neural network-based surface defect detection model, and training the deep neural network-based surface defect detection model to obtain the trained surface defect detection model. The normal image represents the product surface of no defect on this surface.

Abstract: A method for segmenting and denoising a triangle mesh, the method comprising: reading triangle mesh data containing N triangular patches, determining the noise level of the triangle mesh data, and optimizing data at a noise level higher than a preset value; segmenting the triangle mesh data by using a region growing segmentation algorithm, such that a plurality of sub-regions of the triangle mesh data are formed; optimizing the segmented triangle mesh data by using a hole-filling algorithm; and filtering the segmented triangle mesh data by using a denoising algorithm.

Abstract: A method for training a surface defect detection model as well as a method and a system for detecting a surface defect are provided. The method and the system for detecting a surface defect adopt the trained surface defect detection model. The method for training a surface defect detection model includes acquiring a normal image of a product and an external image that is irrelevant to the product and inputting the normal image and the external image into a deep neural network-based surface defect detection model, and training the deep neural network-based surface defect detection model to obtain the trained surface defect detection model. The normal image represents the product surface of no defect on this surface.

Abstract: A method for segmenting and denoising a triangle mesh, the method comprising: reading triangle mesh data containing N triangular patches, determining the noise level of the triangle mesh data, and optimizing data at a noise level higher than a preset value; segmenting the triangle mesh data by using a region growing segmentation algorithm, such that a plurality of sub-regions of the triangle mesh data are formed; optimizing the segmented triangle mesh data by using a hole-filling algorithm; and filtering the segmented triangle mesh data by using a denoising algorithm.