Computer implemented process to enhance edge defect detection and other defects in ophthalmic lenses

A computer-implemented process for creating an object detection model using neural networks to increase inspection efficiency comprising at least one high performance processor, Fast access memory and several parallel graphic processing units, the method comprising:

• an uncompressed high resolution image of the object;
• preprocessing the image by applying smoothing algorithms to enhance defect information without compressing the pixel data;
• Segmenting the pre-processed image and performing dimension normalisation by reconstructing them into square areas, best suited for input to the graphic processing unit;
• applying deep learning algorithms to the optimised images to extract feature information within each image to aid in machine learning and training;
• classifying the extracted and calibrated feature information under several categories through the application of neural networks;
• re-classifying the categories of extracted features from new images generated through application of Generative adversarial networks to the optimised and uncompressed images;
• creating an extensive database of extracted features detected within the images for micro defect inspection in uncompressed images;
• applying neural networks in combination with the domain knowledge database to inspect new devices at high speed and efficiency.