Machine-vision-based bar code scanning for long-range applications

Larry E. Banta; Franz A. Pertl; Charles Rosenecker; Kimberly A. Rosenberry-Friend

doi:10.1117/12.326917

9 October 1998 Machine-vision-based bar code scanning for long-range applications

Larry E. Banta, Franz A. Pertl, Charles Rosenecker, Kimberly A. Rosenberry-Friend

Proceedings Volume 3517, Intelligent Systems in Design and Manufacturing; (1998) https://doi.org/10.1117/12.326917
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

Bar code labeling of products has become almost universal in most industries. However, in the steel industry, problems with high temperatures, harsh physical environments and the large sizes of the products and material handling equipment have slowed implementation of bar code based systems in the hot end of the mill. Typical laser-based bar code scanners have maximum scan distances of only 15 feet or so. Longer distance models have been developed which require the use of retro reflective paper labels, but the labels must be very large, are expensive, and cannot stand the heat and physical abuse of the steel mill environment. Furthermore, it is often difficult to accurately point a hand held scanner at targets in bright sunlight or at long distances. An automated product tag reading system based on CCD cameras and computer image processing has been developed by West Virginia University, and demonstrated at the Weirton Steel Corporation. The system performs both the pointing and reading functions. A video camera is mounted on a pan/tilt head, and connected to a personal computer through a frame grabber board. The computer analyzes the images, and can identify product ID tags in a wide-angle scene. It controls the camera to point at each tag and zoom for a closeup picture. The closeups are analyzed and the program need both a barcode and the corresponding alphanumeric code on the tag. This paper describes the camera pointing and bar-code reading functions of the algorithm. A companion paper describes the OCR functions.

Citation Download Citation

Larry E. Banta, Franz A. Pertl, Charles Rosenecker, and Kimberly A. Rosenberry-Friend "Machine-vision-based bar code scanning for long-range applications", Proc. SPIE 3517, Intelligent Systems in Design and Manufacturing, (9 October 1998); https://doi.org/10.1117/12.326917

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