14. An apparatus to create graphical object classifier data structures comprising: a sample imager configured to record an image of a card object; a region identifier configured to identify graphical objects within the image by: i) determining pixels that correspond to each graphical object of the image; ii) determining a graphical object type of each of the graphical objects; iii) creating a bounding region for each of the graphical objects such that a border of the bounding region is located at a predetermined distance from segments of the respective graphical object; iv) determining an origin of the graphical object; and v) determining a coordinate relative to the origin for each graphical object pixel; and a training processor configured to: i) determine a statistical probability that features are present within each of the graphical objects, each of the features including at least one pixel having coordinates; and ii) for each graphical object type, combine the statistical probabilities for each of the features of the identified graphical objects of that graphical object type into a classifier data structure.
14. An apparatus to create graphical object classifier data structures comprising: a sample imager configured to record an image of a card object; a region identifier configured to identify graphical objects within the image by: i) determining pixels that correspond to each graphical object of the image; ii) determining a graphical object type of each of the graphical objects; iii) creating a bounding region for each of the graphical objects such that a border of the bounding region is located at a predetermined distance from segments of the respective graphical object; iv) determining an origin of the graphical object; and v) determining a coordinate relative to the origin for each graphical object pixel; and a training processor configured to: i) determine a statistical probability that features are present within each of the graphical objects, each of the features including at least one pixel having coordinates; and ii) for each graphical object type, combine the statistical probabilities for each of the features of the identified graphical objects of that graphical object type into a classifier data structure. 17. The apparatus of claim 14 , wherein the sample imager is configured to receive a physical size of the card object, the region identifier is configured to determine a size of the imaged card object, and the training processor is configured to reference the size of the imaged card object to a size of the bounding regions identified for the imaged card object and the physical size of the card object.