Systems, devices, and methods for reading machine-readable characters and human-readable characters

• US 7,546,955 B2
• Filed: 03/16/2007
• Issued: 06/16/2009
• Est. Priority Date: 03/16/2007
• Status: Active Grant

• Current Assignee: Intermec IP Corporation (Honeywell International Inc.)
• Original Assignee: Intermec IP Corporation (Honeywell International Inc.)
• Inventors: Marty, William A., Ackley, H. Sprague, Dean, Daniel
• Primary Examiner(s): Le; Thien Minh
• Assistant Examiner(s): VO, TUYEN KIM
• Application Number:
  US11/687,555
• Publication Number:
  US 20080223935A1
• Time in Patent Office: 823 Days
• Field of Search: 235/462.01, 235/462.08, 235/462.14, 235/462.16, 235/462.45, 235/472.01, 235/472.03
• US Class Current: 235/470
• CPC Class Codes: G06K 7/10544 by scanning of the records by radiation in the optical part of the electromagnetic spectrum
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/1448 based on markings or identifiers characterising the document or the area

Abstract

Systems, devices, and methods for automatic data collection. An automatic data collection system includes an image capture subsystem and a processor subsystem. The automatic data collection system is operable to decode machine-readable symbols in a machine-readable symbol reading mode, and to automatically switch from a machine-readable symbol reading mode to an optical character recognition mode in response to information encoded in a machine-readable symbol. In some embodiments, the automatic data collection system is further operable to perform optical character recognition on human-readable symbols in a human-readable symbol reading mode.

Claims

1. A method of operating an automatic data collection device, the method comprising:

reading a machine-readable symbol;

determining a location of a first number of human-readable symbols from information encoded in the machine-readable symbol;

determining a location of a second number of human-readable symbols from information encoded in the machine-readable symbol, the second number of human-readable symbols spaced from the first number of human-readable symbols;

reading the first number of human-readable symbols;

reading the second number of human-readable symbols; and

verifying information contained in the first number of human-readable symbols based at least in part on information contained in the second number of human-readable symbols.

2. The method of claim 1, further comprising:

changing from a machine-readable symbol mode to a character recognition mode in response to information encoded in the machine-readable symbol.

3. The method of claim 1 wherein reading the machine-readable symbol includes capturing an image of the machine-readable symbol.

4. The method of claim 3 wherein reading the machine-readable symbol includes decoding the machine-readable symbol based on the captured image of the machine-readable symbol.

5. The method of claim 1 wherein reading the first and the second number of human-readable symbols includes capturing an image of the first and the second number of human-readable symbols.

6. The method of claim 1 wherein reading the first and the second number of human-readable symbols includes capturing a respective image of each of the first and the second number of human-readable symbols.

7. The method of claim 1 wherein verifying information read from the first number of human-readable symbols is based at least in part on information read from the second number of human-readable symbols includes performing error detection and/or correction on the information read from the first number of human-readable symbols using error correction information encoded in the second number of human-readable symbols.

8. An automatic data collection system, comprising:

an image subsystem operable to capture images; and

a processor subsystem configured to decode a machine-readable symbol acquired by the image subsystem, determine a first location of a first number of human-readable symbols from information encoded in the machine-readable symbol, determine a second location of a second number of human-readable symbols from information encoded in the machine-readable symbol, the second number of human-readable symbols spaced from the first number of human-readable symbols, read the first number of human-readable symbols at the first location, read the second number of human-readable symbols at the second location, and verify information read from the first number of human-readable symbols based at least in part on information read from the second number of human-readable symbols.

9. The automatic data collection system of claim 8 wherein the processor subsystem includes a processor operable to execute instructions and a memory that stores instructions that causes the processor to determine a location of a first number of human-readable symbols from information encoded in the machine-readable symbol by determining a location of the first number of human-readable symbols in an image that includes the machine-readable symbol.

10. The automatic data collection system of claim 8 wherein the processor subsystem includes a processor operable to execute instructions and a memory that stores instructions that causes the processor to verify information read from the first number of human-readable symbols based at least in part on information read from the second number of human-readable symbols by performing error detection and/or correction on the information read from the first number of human-readable symbols using error correction information encoded in the second number of human-readable symbols.

11. The automatic data collection system of claim 8 wherein the processor subsystem is configured to read the first and the second number of human-readable symbols by performing optical character recognition.

12. The automatic data collection system of claim 8 wherein the image subsystem includes a two-dimensional image capture device.

13. A method of automatic data collection from objects bearing a machine-readable symbol, a first number of human-readable symbols, and a second number of human-readable symbols spaced from the first number of human-readable symbols, the method comprising:

automatically reading the first number of human-readable symbols;

automatically reading the second number of human-readable symbols; and

verifying information read from the first number of human-readable symbols based at least in part on information read from the second number of human-readable symbols;

automatically reading the machine-readable symbol before automatically reading the first and the second number of human-readable symbols;

determining a location of the first number of human-readable symbols from information encoded in the machine-readable symbol; and

determining a location of the second number of human-readable symbols from information encoded in the machine-readable symbol.

14. The method of claim 13, further comprising:

automatically changing from a machine-readable symbol mode to a character recognition mode in response to information encoded in the machine-readable symbol.

15. The method of claim 13, wherein determining a location of the first number of human-readable symbols from information encoded in the machined-readable symbol includes determining a location of the first location of human-readable symbols in an image from the information encoded in the machine-readable symbol, and wherein determining a location of the second number of human-readable symbols from information encoded in the machine-readable symbol includes determining a location of the second number of human-readable symbols in the image from the information encoded in the machine-readable symbol.

16. The method of claim 13 wherein automatically reading the machine-readable symbol includes capturing an image of the machine-readable symbol.

17. The method of claim 16 wherein automatically reading the machine-readable symbol includes decoding the machine-readable symbol based on the captured image of the machine-readable symbol.

18. The method of claim 16 wherein automatically reading the first and the second number of human-readable symbols includes capturing an image of the first and the second number of human-readable symbols.

19. The method of claim 16 wherein automatically reading the first and the second number of human-readable symbols includes capturing a respective image of each of the first and the second number of human-readable symbols.

20. The method of claim 13 wherein verifying information read from the first number of human-readable symbols based at least in part on information read from the second number of human-readable symbols includes performing error detection and/or correction on the information read from the first number of human-readable symbols using error correction information encoded in the second number of human-readable symbols.

21. An automatic data collection system, comprising:

an image capture subsystem operable to capture images; and

a processor subsystem configured to read a first number of human-readable symbols, read a second number of human-readable symbols, and verify information read from the first number of human-readable symbols based at least in part on information read from the second number of human-readable symbols;

wherein the processor subsystem is further configured to read a machine-readable symbol before reading the first and the second number of human-readable symbols, and determine a location of the first number of human-readable symbols from information encoded in the machine-readable symbols; and

wherein the processor subsystem is further configured to determine a location of the second number of human-readable symbols from information encoded in the machine-readable symbol.

22. The automatic data collection system of claim 21 wherein the processor subsystem is further configured to automatically change from a machine-readable symbol mode to a character recognition mode in response to information encoded in the machine-readable symbol.

23. The automatic data collection system of claim 21 wherein the processor subsystem is further configured to perform error detection and/or correction on the information read from the first number of human-readable symbols using error detection and/or information encoded in the second number of human-readable symbols.