Automatic optical inspection using hybrid imaging system

A system comprising:

• one or more teacher modules, wherein each teacher module comprises a dual-scanning system comprising a low-quality scanning system and a high-quality scanning system configured to obtain low-quality and high-quality images of a scanned product, respectively;
• a plurality of student modules, wherein each student module comprising the low-quality scanning system;
• a model generator configured to generate a prediction model, wherein the prediction model is configured to predict, based on a low-quality image of a product, an enhanced-quality image of the product, wherein the enhanced-quality image has a higher quality than a quality of the low-quality image;
• and
• a defects detector configured to detect defects using automated optical inspection of an image of products, wherein said defects detector is configured to detect defects in enhanced-quality images predicted by the prediction model,
• wherein at least one of the teacher modules is configured to perform results evaluation of defects detection with the teacher module, wherein said performing results evaluation comprises:
• utilizing the high-quality scanning system to capture a high-quality image of the product;
• performing defects detection on the high-quality image;
• and
• comparing results between said performing defects detection on the high-quality image and said performing defects detection on the enhanced-quality image.

A computer program product comprising a non-transitory computer readable storage medium retaining program instructions, which program instructions when read by a processor, cause the processor to perform:

• obtaining a prediction model, wherein the prediction model is configured to predict enhanced-quality images of products based on low-quality images of the products, wherein the prediction model is generated based on pairs of images obtained by a dual-scanning system comprising a low-quality scanning system and a high-quality scanning system;
• utilizing the low-quality scanning system to capture a low-quality image of a product;
• predicting, based on the low-quality image of the product and using the prediction model, an enhanced-quality image of the product, wherein the enhanced-quality image has a higher quality than a quality of the low-quality image;
• performing defects detection on the enhanced-quality image without utilizing the high-quality scanning system;
• and
• performing results evaluation of defects detection with a teacher module, wherein said performing results evaluation comprises:
• performing defects detection on a high-quality image captured by the high-quality scanning system;
• and
• comparing results between said performing defects detection on the high-quality image and said performing defects detection on the enhanced-quality image.