Xerox Corporation

Per-Kristian G Halvorsen

Ronald M Kaplan

Todd A Cass

Daniel P Huttenlocher

M Margaret Withgott

Dan S Bloomberg

Douglass R Cutting

Steven C Bagley

Jan O Pedersen

Ramana B Rao

Martin Kay

Daniel Gureasko Bobrow

Eric Allan Bier

William M Newman

John W Tukey

John Seely Brown

Lauri J Karttunen

Ramana R Rao

A method and apparatus for applying morphological image criteria that identify image units in an undecoded document image having significant information content, and for retrieving related data that supplements the document either from elsewhere within the document or a source external to the document. The retrieved data can result from character code recognition or template matching of the identified significant image units, or the retrieved data can result directly from an analysis of the morphological image characteristics of the identified significant image units. A reading machine can allow a user to browse and select documents or segments thereof, and to obtain interactive retrieval of documents and supplemental data.

Method and apparatus for supplementing significant portions of a

The present invention solves a number of problems in using stems (canonical indicators of word meanings) in full-text retrieval of natural language documents, and thus permits recall to be improved without sacrificing precision. It uses various arrangements of finite-state transducers to accurately encode a number of desirable ways of mapping back and forth between words and stems, taking into account both systematic aspects of a language's morphological rule system and also the word-by-word irregularities that also occur. The techniques described apply generally across the languages of the world and are not just limited to simple suffixing languages like English. Although the resulting transducers can have many states and transitions or arcs, they can be compacted by finite-state compression algorithms so that they can be used effectively in resource-limited applications. The invention contemplates the information retrieval system comprising the novel finite state transducer as a database and a processor for responding to user queries, for searching the database, and for outputting proper responses, if they exist, as well as the novel database used in such a system and methods for constructing the novel database.

Finite-state transduction of related word forms for text indexing and

A method and apparatus for excerpting and summarizing an undecoded document image, without first converting the document image to optical character codes such as ASCII text, identifies significant words, phrases and graphics in the document image using automatic or interactive morphological image recognition techniques, document summaries or indices are produced based on the identified significant portions of the document image. The disclosed method is particularly adept for improvement of reading machines for the blind.

Method and apparatus for summarizing a document without document image

A method and apparatus for processing a document image, using a programmed general or special purpose computer, includes forming the image into image units, and at least one image unit classifier of at least one of the image units is determined, without decoding the content of the at least one of the image units. The classifier of the at least one of the image units is then compared with a classifier of another image unit. The classifier may be image unit length, width, location in the document, font, typeface, cross-section, the number of ascenders, the number of descenders, the average pixel density, the length of the top line contour, the length of the base contour, the location of image units with respect to neighboring image units, vertical position, horizontal inter-image unit spacing, and so forth. The classifier comparison can be a comparison with classifiers of image units of words in a reference table, or with classifiers of other image units in the document. Equivalent classes of image units can be generated, from which word frequency and significance can be determined. The image units can be determined by creating bounding boxes about identifiable segments or extractable units of the image, and can contain a word, a phrase, a letter, a number, a character, a glyph or the like.

Methods and apparatus for selecting semantically significant images in a

Methods and apparatus of processing an undecoded document image in a digital computer to modify the document image so as to emphasize semantically significant portions without first converting the document image to character codes. The document image is segmented into image units, and morphological image characteristics of the image units are evaluated to identify significant image units for emphasis. In one embodiment, the significant image units are emphasized by modifying at least one shape characteristic of the significant image units using at least one uniform morphological bitmap operation applied to the entire image unit bitmaps corresponding to the significant image units.

Methods and apparatus for automatic modification of semantically

A method and apparatus for determining word frequency from a document without first converting the document to character codes. The method includes morphological image processing to determine word unit characteristics for placement into equivalence classes utilizing non-content based information. Word shape representations are preferably determined and compared to define equivalent word units.

Method and apparatus for determining the frequency of words in a

An information retrieval system and method are provided in which an operator inputs one or more query words which are used to determine a search key for searching through a corpus of documents, and which returns any matches between the search key and the corpus of documents as a phrase containing the word data matching the query word(s), a non-stop (content) word next adjacent to the matching word data, and all intervening stop-words between the matching word data and the next adjacent non-stop word. The operator, after reviewing one or more of the returned phrases can then use one or more of the next adjacent non-stop-words as new query words to reformulate the search key and perform a subsequent search through the document corpus. This process can be conducted iteratively, until the appropriate documents of interest are located. The additional non-stop-words from each phrase are preferably aligned with each other (e.g., by columnation) to ease viewing of the 'new' content words.

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Los Altos, CA, United States of America

Per-Kristian G Halvorsen