Pallet tag classification for improved text recognition accuracy

A method for pallet text recognition with improved accuracy, the method comprising:

• receiving a portion of an image associated with a pallet tag associated with a pallet within a retail facility, the image generated by an image capture device within the retail facility;
• executing a pallet text manager comprising at least a neural network (NN) recognition model, an NN classification model, and an NN location recognition model, wherein the NN recognition model is trained for at least small text recognition and the NN classification model is trained for at least pallet attribute recognition, the pallet text manager being operable to:
• detecting, using the NN recognition model, a plurality of lines of text associated with the portion of the image of the pallet tag associated with the pallet, wherein the plurality of lines of text are associated with a first tag format, and wherein the image comprises a plurality of pixels;
• determining, using the NN recognition model, whether one or more lines of text within the plurality of lines of text are tilted within a portion of the image, and based on the determination that one or more the plurality of lines of text are tilted:
• generating a plurality of text-related values associated with a plurality of text-related pixels in the portion of the image and a plurality of non-text related values associated with a plurality of non-text related pixels in the portion of the image, the plurality of text-related values corresponding to alphanumeric characters in a tilted line of text;
• and
• enclosing the plurality of text-related values within a quadrilateral shaped bounding box, wherein the quadrilateral shaped bounding box encloses the plurality of text-related pixels detected on the pallet tag;
• classifying, using the NN classification model, a type of the pallet tag based on the plurality of lines of text, the type of the pallet tag corresponding to the first tag format;
• selecting, using the NN classification model, a set of qualified lines of text within the plurality of lines of text using the first tag format associated with the type of the pallet tag by applying a stored first set of rules associated with the first tag format to identify a qualified lines of text, wherein the qualified lines of text comprising a pallet attribute;
• extracting a set of pallet attribute values from the set of qualified lines of text, the set of pallet attribute values comprising a pallet identifier (ID);
• and
• mapping the set of pallet attribute values to a location ID in a pallet entry within a pallet attributes table stored in a data storage device, wherein the location ID identifies a location of the pallet within the retail facility, wherein the location ID is being generated by the NN location recognition model, and wherein the location of the pallet is presented to a user via a user interface device.

One or more computer storage devices having computer-executable instructions stored thereon, which, upon execution by a computer, cause the computer to perform operations comprising:

• obtain a portion of an image associated with a pallet tag detected on a pallet within a retail facility, the image generated by an image capture device within the retail facility;
• execute a pallet text manager comprising at least a neural network (NN) recognition model, an NN classification model, and an NN location recognition model, wherein the NN recognition model is trained for at least small text recognition and the NN classification model is trained for at least pallet attribute recognition, the pallet text manager being operable to:
• detect, using the NN recognition model, a plurality of lines of text associated with the portion of the image of the pallet tag associated with the pallet, wherein the plurality of lines of text are associated with a first tag format, and wherein the portion of the image comprises a plurality of pixels;
• determine, using the NN recognition model, whether one or more lines of text within the plurality of lines of text are tilted within the portion of the image, and based on the determination that one or more the plurality of lines of text are tilted:
• generate a plurality of text-related values associated with a plurality of text-related pixels in the portion of the image and a plurality of non-text related values associated with a plurality of non-text related pixels in the portion of the image, the plurality of text-related values corresponding to alphanumeric characters in a tilted line of text;
• and
• enclose the plurality of text-related values within a quadrilateral shaped bounding box, wherein the quadrilateral shaped bounding box encloses a plurality of lines of text detected on the pallet tag;
• classify, using the NN classification model, a type of the pallet tag based on the plurality of lines of text, the type of the pallet tag corresponding to the first tag format;
• select, using the NN classification model, a set of qualified lines of text within the plurality of lines of text using the first tag format associated with the type of the pallet tag by applying a stored first set of rules associated with the first tag format to identify a qualified lines of text, wherein the qualified lines of text comprising a pallet attribute;
• extract a set of pallet attribute values from the set of qualified lines of text, the set of pallet attribute values comprising a pallet identifier (ID);
• and
• map the set of pallet attribute values to a location ID in a pallet entry within a pallet attributes table stored in a data storage device, wherein the location ID identifies a location of the pallet within the retail facility, wherein the location ID is being generated by the NN location recognition model, and wherein the location of the pallet is presented to a user via a user interface device.