Barcode-enhanced documents are used in office automation and in applications involving shipping manifests, vehicle registration forms, photo-ID, etc. They consist of human readable text and machine readable barcodes, which duplicates the text in a secure machine-readable form. Two-dimensional barcodes are used when it is beneficial to encode a large amount of data. The advantage of barcode-enhanced document over OCR is that the rejection and misdecode rates are several orders of magnitude smaller. This paper analyzes the performance of 2-D barcode-enhanced documents, characterized by the rates of correct decode, rejection, and misdecode of the 2-D barcode. Primarily using PDF417 as an example, we show how these rates are determined by the parameters used in the encoding process and the decoder design, and from the environment. We find that in real-world applications the misdecode rates are extremely low, and thus for all practical purposes the limiting parameter is the rejection rate.
Imaging bar-code scanners may use an edge-detection algorithm as the first step to locate a bar code in the image it acquires. This is also likely a step that consumes a significant amount of the total bar-code detection time. A simple but efficient special-purpose edge-detection algorithm is introduced that makes use of the special properties expected from a bar-code image.