Synthetic image generation for surface anomaly detection

A method for detecting surface anomalies on an object, the method comprising:

• receiving two or more images of the object taken at different ambient conditions by one or more cameras, the two or more images comprising one or more of two different image types, wherein the different ambient conditions comprise one or more of different ambient temperatures or different ambient humidities;
• calculating, with a trained image translation model, for each of the two or more images, a paired image, wherein the paired image comprises the other of the two different image types;
• and
• determining whether the object contains a surface anomaly based on the received two or more images, the calculated paired images, and the different ambient conditions.

A system comprising:

• a computing device comprising:
• non-transitory memory comprising computer-readable instructions for:
• receiving unpaired image data of an object, the unpaired image data comprising two different image types representing two different wavelength ranges of electromagnetic radiation (EMR);
• predicting missing image data to generate paired image data of the two different image types;
• determining whether the object contains a surface anomaly based on the paired image data;
• adjusting the predicted missing image data based on changes in one or more ambient conditions, wherein the one or more ambient conditions comprise one or more of ambient temperature, ambient lighting, and ambient humidity;
• and
• a processing unit configured to execute the computer-readable instructions.