Abstract:
Method and systems are provided for recognizing characters in an original image. The images received in the system as a set of pixels representing the original image as a character skeleton and a chaincore representation thereof. A skeleton intersection points are identified using a basis for determining a cutting points in the chaincore contours compared to the cutting points are then used to define cutting lines for segleg the original image into distinct segments. The segments are analyzed with respect to their geometric properties individually and relative to adjacent to other segments for determination that select ones of the segments may be combined wherein the combination is expected to have a high probability of conformance to a likely a digit or character. Verification that the combined string is a recognizable digit or character is accomplished using a convolutional neural network digit recognizer.
Abstract:
A device for registration of content in a filled-out application form is disclosed. The device is configured for scanning at least one portion of the filled-out application form. The device is configured for extracting filled-out content from the scanned form. The geometrical features of the master form are retrieved. The master form includes one or more anchor fields. Each anchor field has one or more anchor zones and at least one anchor segment. At least one anchor segment has global adjustment parameters and geometrical features. The extracted filled-out content is related to the retrieved geometrical features of a master form to create a new geometrical representation of the extracted filled-out content of the scanned application form. The new representation of the filled-out content based on the global adjustment parameters for the at least one anchor segment is globally adjusted. The globally adjusted filled-out content based on the geometrical features for the anchor segments is locally adjusted.