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Application of Generating Adversarial Networks in High-light Removal of Wheel Hub Surface

In the detection of wheel hub surface defect, the clear defect feature is a premise that the algorithm can correctly detect, and the surface of wheel hub often has a great influence on quality of image due to the high reflective property, which is a challenging task. Through research, it has found that the traditional metal surface high-light removal method has poor high-light removal effect and damages the characteristics of highlight areas. In order to find a high-light removal method that can restore the characteristics of the reflective area, we use pix2pix as a high-light removal algorithm, and propose a method of generating adversarial networks to remove the surface reflection of wheel hub. Our related experiments show that this method has achieved good results on the wheel hub high-light data set, and can better recover the surface defect features in high-light area.