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.
Patent No.:
Date of Patent:
Jul. 01, 2003
Filed:
May. 23, 2000
Slawomir B. Wesolkowski, Kitchener, CA;
Cameron W. Woloshyn, Kitchener, CA;
Khaled S. Hassanein, Waterloo, CA;
NCR Corporation, Dayton, OH (US);
Abstract
A method of processing a document comprises the steps of (a) scanning a document to obtain gray scale image data associated with the document, (b) generating a two-dimensional histogram based upon the gray scale image data obtained in step (a), (c) applying a clustering algorithm to the two-dimensional histogram to determine a set of cluster center parameters associated with a first cluster of pixels and a set of cluster center parameters associated with a second cluster of pixels, (d) parameterizing a threshold curve associated with a binarization program based upon the set of cluster center parameters associated with the first cluster of pixels and the set of cluster center parameters associated with cluster of pixels, and (e) applying the binarization program to the gray scale image data associated with the document using the parameterized threshold curve obtained in step (d) to provide a binarized image data representative of a binary image of the document. Preferably, step (d) includes the steps of (d- ) calculating an average value associated with the first and second clusters of pixels, and (d- ) parameterizing at least a portion of the threshold curve based upon the average value calculated in step (d- ). The clustering algorithm includes a k-means clustering algorithm. The one cluster of pixels is representative of background of the document and the other cluster of pixels is representative of foreground of the document. One cluster of pixels is located above the other cluster of pixels. The above cluster of pixels is representative of background of the document and the other cluster of pixels is representative of foreground of the document.