Xerox Corporation

Lakshmi Dasari

Dan S Bloomberg

Henry W Sang, Jr

A method and apparatus for detection of highlighted regions of a document. A document containing highlighted regions is scanned using a gray scale scanner. Morphology and threshold reduction techniques are used to separate highlighted and non-highlighted portions of the document. Having separated the highlighted and non-highlighted portions, optical character recognition (OCR) techniques can then be used to extract text from the highlighted regions.

Detection of highlighted regions

A method of apparatus for automatic page orientation of a scanned image which compares the number of character ascending pixels to the number of character descending pixels in the image to determine if the image is properly aligned or is 90.degree. or 180.degree. out of orientation. The method and apparatus includes morphologically processing the bitmap of the scanned image using structuring elements for isolating the character ascenders and descenders. When page orientation is improper, the bitmap image of the scanned image is rotated to correct the misalignment.

Rapid detection of page orientation

An image markup detection device and method identifies and extracts markup lines and regions marked automatically or interactively by a user with an ordinary pen or pencil. Only morphological image processing operations on a scanned source image are used, resulting in the extrapolation of markup lines and marked region. The markup lines are either extracted from the image, or the background information of the image (e.g., text) is removed, leaving only the markup lines. The marked region can then be printed, transferred or otherwise processed.

Method and apparatus for image hand markup detection using morphological

A method and apparatus for detection of highlighted regions of a document. A document containing highlighted regions is scanned using a gray scale scanner. Morphology and threshold reduction techniques are used to separate highlighted and non-highlighted portions of the docment. Having separated the highlighted and non-highlighted portions, optical character recognition (OCR) techniques can then be used to extract text from the highlighted regions.

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Palo Alto, CA, United States of America

Lakshmi Dasari