Abstract: An item recognition system and method which is particularly suited for automating entry of items too small to carry readable bar code labels. The system includes a camera which digitizes the image to produce a digitized image and a gray-scale digitized image. A binary image of the gray-scale image is then produced from which the computer records an image of the item, and a computer coupled to the camera which digitizes the image to produce a digitized image and a gray-scale digitized image. A binary image of the gray-scale image is then produced from which the computer identifies the item from the binary image and obtains the price from a price-lookup file.

Abstract: A knowledge-based document analysis system and method for identifying and decomposing constrained and unconstrained images of documents is disclosed. Low level features are extracted within bitonal and grayscale images. Low level features are passed to a document classification means which forms initial hypotheses about the document class. For constrained documents, the document analysis system sorts through various models to determine the exact type of document and then extracts the relevant fields for character recognition. For unconstrained documents, through the use of a blackboard architecture which includes a knowledge database and knowledge sources, the document analysis means creates information and hypotheses to identify and locate relevant fields within the document. These fields are then sent for optical character recognition.