Image processing systems and methods and associated automatic controls

A method for controlling an output device based on a normalized image of a face generated from a captured non-normalized image of the face comprising:

• generating a random dataset of images representing synthetic non-normalized photographs of human faces and backgrounds;
• generating an output dataset of synthetic normalized photographs by:
• for each synthetic non-normalized photograph:
• removing variations to generate a normalized image of each human face;
• and
• removing the backgrounds surrounding each human face for each normalized image, removing the backgrounds comprising:
• calculating a symmetric loss for each image;
• calculating background statistics for each image;
• preparing a positive dataset of a first subset of the images with:
• a symmetric loss in a first lower range;
• a background color in a first higher range;
• and
• a background diversity in a second lower range;
• preparing a negative dataset of a second subset of the images with:
• the symmetric loss in a higher range greater than the first lower range;
• the background color in a third lower range than the second higher range;
• and
• the background diversity in a third range higher than the second lower range;
• generating a trained linear classifier separating the positive dataset and the negative dataset for each image;
• generating a separation plan from the trained linear classifier;
• and
• learning a linear control function to generate each normalized image based on the foregoing;
• generating a training dataset including the random dataset and the output dataset;
• training a neural network to generate normalized photographs from non-normalized photographs using the training dataset;
• receiving a non-normalized facial image of an individual;
• applying the neural network to generate a normalized facial image from the non-normalized facial image;
• and
• controlling an output device based on the normalized image of the individual.