Training an image processing neural network without human selection of features

An apparatus for processing images, the apparatus comprising:

• a storage device configured to store a training set comprising images labeled with two or more classifications;
• a processor configured to execute an image processing toolbox comprising a plurality of image transforms;
• a plurality of feature extraction pipelines, each feature extraction pipeline comprising a sequence of image transforms;
• and
• a corresponding plurality of first stage classifiers coupled to the plurality of feature extraction pipelines;
• wherein the plurality of feature extraction pipelines were generated by:
• generating a random set of feature extraction pipelines, each feature extraction pipeline comprising a sequence of image transforms randomly selected from the image processing toolbox and randomly selected control parameters associated with the sequence of image transforms,
• coupling a first stage classifier to an output of each feature extraction pipeline, and
• executing a genetic algorithm to conduct genetic modification of each feature extraction pipeline and train each first stage classifier on the training set.

An apparatus for training an image processing neural network without human selection of features, the apparatus comprising:

• a storage device configured to store a training set comprising images labeled with two or more classifications;
• a processor configured to execute an image processing toolbox comprising a plurality of image transforms;
• the processor configured to generate a random set of feature extraction pipelines, each feature extraction pipeline comprising a sequence of image transforms randomly selected from the image processing toolbox and randomly selected control parameters associated with the sequence of image transforms;
• the processor configured to couple a first stage classifier to an output of each feature extraction pipeline;
• and
• the processor configured to execute a genetic algorithm to conduct genetic modification of each feature extraction pipeline and train each first stage classifier on the training set.