The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 14, 2008

Filed:

Mar. 29, 2002
Applicants:

Ben F. Bruce, Arlington, TX (US);

Linda J. Kessler, Washington, DC (US);

Inventors:

Ben F. Bruce, Arlington, TX (US);

Linda J. Kessler, Washington, DC (US);

Assignee:

Siemens Energy & Automation, Alpharetta, GA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
Abstract

A method of processing an image containing written information according to the invention includes the steps of scanning a surface of an object to obtain an image of the surface represented by image data, analyzing the image data to determine locations of one or more regions with written indicia on the surface, where indicia may include logos, stamps, meter marks, alphanumeric information, labels or other distinctive marks, creating one or more sub-images substantially limited to the dimensions of the indicia-bearing regions, transmitting the sub-images from a first computer or process used to create the sub-images to a second computer or process, and further analyzing the sub-images at the second computer or process, such as by OCR, to decode the written indicia in the sub-images. By transmitting the sub-images, preferably in combination with position data indicating where each sub-image was on the original image, the scanned written indicia can be decoded automatically or manually without having to transmit the original image from one computer or process to another. This is particularly important when the image data is a grayscale or color image that is much larger than a black and white (binary) image of the same dimensions.


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