An encoding operation encodes binary data that is then embedded in an iconic, or size-reduced, version of an original text image, in a position in the iconic image that replaces a text portion in the original text image. The encoding operation produces rectangular blocks that have a foreground color and size dimensions proportional to the iconic image so that when placed in the iconic image in horizontal lines, the blocks appear to a viewer to be representative of the text portion of the original image that they replace. Exemplary encoding operations are described, including operations based on run-length limited encoding. A second message may be encoded in the background color regions that separate the blocks. The message carried by the binary data may be any information suitable for a particular application, and need not be restricted to information about or related to the original image. The encoding operation is designed to be robust for decoding purposes regardless of the resolution at which a copy of the iconic image is subsequently rendered. The iconic image may be printed in a suitable place (e.g., the margin or other background region) in the original text image so that a text image so annotated will then always carry the embedded data in subsequent copies made from the annotated original. The iconic image alone may also be used in printed form or as part of a graphical user interface as a surrogate for the original text image in a variety of applications.

Embedding encoded information in an iconic version of a text image

A system for spacing, storing and recognizing electronic representations of handwriting and printing comprises a central processing unit that couples with a display device, an input device, and a memory. The memory includes means for spacing ink stroke representations, means for recognizing outline elements, means for performing deferred recognition, means for highlighting drawing areas and means for storing and displaying ink stroke representations. These means operate together to provide a pen-based or graphics oriented computer system with improved performance and added functionality for manipulating the space between ink stroke representations. The preferred embodiment of the present invention comprises several novel methods that provide this functionality including: a method for managing space between ink stroke representations, a method for displaying drawing elements in a visually distinct manner, a method for recognizing bullets and dashes, a method for storing ink stroke representations, a method for displaying and printing ink stroke representations, and a method for performing deferred character or word recognition.

System and methods for spacing, storing and recognizing electronic representations of handwriting printing and drawings

A character recognition system or the like in which character identities are stored in accordance with a hierarchical order established during processing to separate text image areas from non-text image areas. To separate text image areas from non-text image areas, blocks of pixels are selected from pixel image data by outlining contours of connected components in the pixel image data, determining whether the outlined connected components include text units or non-text units, selectively connecting text units widthwisely to form text lines, and selectively connecting text lines vertically to form text blocks. After blocks of pixels have been so selected, text blocks are segmented into lines of pixel image data, and characters are cut from the lines of pixel image data so obtained. If desired, the characters may be cut by a two-step cutting process in which non-touching and non-overlapping characters are first cut out, and touching characters are then cut out. The cut-out characters are then recognized, and the characters are stored in accordance with an order established during the block selecting process.

Method and apparatus for character recognition

A method for determining the boundaries of a symbol or word string within an image, including the steps of determining page orientation, isolating symbol strings from adjacent symbol strings, establishing a set of boundaries or references with respect to which measurements about, or further processing of, the symbol string may be made.

Method for determining boundaries of words in text

A method comprising enabling a user to define a redaction of a part of a document in a corpus of documents, the redaction definition including a scope defining a range of documents in the corpus to which the redaction applies.

A method and apparatus to provide a unified redaction system

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

Several approaches have previously been taken for identifying document image skew. At issue are efficiency, accuracy, and robustness. We work dire ctly with the image, maximizing a function of the number of ON pixels in a scanline. Image rotation is simulated by either vertical shear or accumulation of pixel counts along sloped lines. Pixel sum differences on adjacent scanlines reduce isotropic background noise from non-text regions. To find the skew angle, a succession of values of this function are found. Angles are chosen hierarchically, typically with both a coarse sweep and a fine angular bifurcation. To inc rease efficiency, measurements are made on subsampled images that have been pre-filtered to m aximize sensitivity to image skew. Results are given for a large set of images, including multiple and unaligned text columns, graphics and large area halftones. The measured intrinsic angular error is inversely proportional to the number of sampling points on a scanline. This method does not indicate when text is upside-down, and it also requires sampling the function at 90 degrees of rotation to measure text skew in landscape mode. However, such text orientation can be determined (as one of four directions) by noting that roman characters in all languages have many more ascenders than descenders, and using morphological operations to identify such pixels. Only a small amount of text is required for accurate statistical determination of orientation, and images without text are identified as such.

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Measuring document image skew and orientation

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° or 180° 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.

Lakshmi Dasari

Papers

Detection of highlighted regions

Measuring document image skew and orientation

Rapid detection of page orientation