CA2041922A1 - Dense aggregative hierarchical techniques for data analysis - Google Patents

Dense aggregative hierarchical techniques for data analysis

Info

Publication number
CA2041922A1
CA2041922A1 CA2041922A CA2041922A CA2041922A1 CA 2041922 A1 CA2041922 A1 CA 2041922A1 CA 2041922 A CA2041922 A CA 2041922A CA 2041922 A CA2041922 A CA 2041922A CA 2041922 A1 CA2041922 A1 CA 2041922A1
Authority
CA
Canada
Prior art keywords
hierarchical
exhaustive
aggregative
embedding
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CA2041922A
Other languages
French (fr)
Other versions
CA2041922C (en
Inventor
James V. Mahoney
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xerox Corp
Original Assignee
Xerox Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xerox Corp filed Critical Xerox Corp
Publication of CA2041922A1 publication Critical patent/CA2041922A1/en
Application granted granted Critical
Publication of CA2041922C publication Critical patent/CA2041922C/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/42—Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
    • G06V10/422—Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation for representing the structure of the pattern or shape of an object therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/457—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by analysing connectivity, e.g. edge linking, connected component analysis or slices

Abstract

A body of data is operated upon hierarchically in such a way that, at one or more levels of the hierarchy, the number of aggregative data items produced is not substantially less than the number produced at the preceding level.
The body of data can be an image, so that each aggregative data item indicates an attribute of a distinct image region. Such attributes include presence of a single connected component or properties of a component such as width, orientation and curvature. A class of abstract computation structures, called exhaustive hierarchical structures, is introduced in which such dense or exhaustive hierarchical aggregative data analysis processes can be embedded. The embedding of exhaustive hierarchical analysis in a computation structure of this class is analogous, and in some implementations similar in processing efficiency, to the embedding of conventional hierarchical aggregative data analysis processes in tree structures. The exhaustive hierarchical embedding introduced analyzes extensively overlapping regions in a manner that places minimum demands on the number of communication links, memory resources, and computing power of the individual processing units. Specifically, the embedding scheme is a general scheme for mapping locations in an array into nodes at two adjacent levels of a binary exhaustive hierarchical structure. The scheme establishes positional relations in the array that correspond to parent-child relations at a given level in the exhaustive hierarchical computing structure; these positional relations are uniform power-of-two offsets in each array dimension at a given hierarchical level. Consequently, this exhaustive hierarchical analysis can be implemented efficiently using conventional communication techniques, including hypercube and grid techniques, on a massively parallel processor. To minimize memory requirements, hierarchical results at each location can be encoded across all levels.
CA002041922A 1990-06-08 1991-05-07 Dense aggregative hierarchical techniques for data analysis Expired - Fee Related CA2041922C (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US535,796 1990-06-08
US07/535,796 US5280547A (en) 1990-06-08 1990-06-08 Dense aggregative hierarhical techniques for data analysis

Publications (2)

Publication Number Publication Date
CA2041922A1 true CA2041922A1 (en) 1991-12-09
CA2041922C CA2041922C (en) 1995-07-18

Family

ID=24135802

Family Applications (1)

Application Number Title Priority Date Filing Date
CA002041922A Expired - Fee Related CA2041922C (en) 1990-06-08 1991-05-07 Dense aggregative hierarchical techniques for data analysis

Country Status (4)

Country Link
US (1) US5280547A (en)
EP (1) EP0460970A2 (en)
JP (1) JPH04296985A (en)
CA (1) CA2041922C (en)

Families Citing this family (40)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5359724A (en) * 1992-03-30 1994-10-25 Arbor Software Corporation Method and apparatus for storing and retrieving multi-dimensional data in computer memory
GB9217361D0 (en) * 1992-08-14 1992-09-30 Crosfield Electronics Ltd Methods and apparatus for generating graphics patterns
US5408670A (en) * 1992-12-18 1995-04-18 Xerox Corporation Performing arithmetic in parallel on composite operands with packed multi-bit components
US5450603A (en) * 1992-12-18 1995-09-12 Xerox Corporation SIMD architecture with transfer register or value source circuitry connected to bus
US5651121A (en) * 1992-12-18 1997-07-22 Xerox Corporation Using mask operand obtained from composite operand to perform logic operation in parallel with composite operand
US5375080A (en) * 1992-12-18 1994-12-20 Xerox Corporation Performing arithmetic on composite operands to obtain a binary outcome for each multi-bit component
EP0603425A1 (en) * 1992-12-22 1994-06-29 International Business Machines Corporation Representation of n-ary trees
US5533148A (en) * 1993-09-30 1996-07-02 International Business Machines Corporation Method for restructuring physical design images into hierarchical data models
JP2812168B2 (en) * 1993-12-27 1998-10-22 松下電器産業株式会社 Shape data compression method and shape data decompression method
JP3335009B2 (en) * 1994-09-08 2002-10-15 キヤノン株式会社 Image processing method and image processing apparatus
US5793371A (en) 1995-08-04 1998-08-11 Sun Microsystems, Inc. Method and apparatus for geometric compression of three-dimensional graphics data
US5842004A (en) * 1995-08-04 1998-11-24 Sun Microsystems, Inc. Method and apparatus for decompression of compressed geometric three-dimensional graphics data
US6747644B1 (en) 1995-08-04 2004-06-08 Sun Microsystems, Inc. Decompression of surface normals in three-dimensional graphics data
US5832475A (en) * 1996-03-29 1998-11-03 International Business Machines Corporation Database system and method employing data cube operator for group-by operations
US6216168B1 (en) * 1997-03-17 2001-04-10 Cabletron Systems, Inc. Perspective-based shared scope address resolution method and apparatus
AUPO886397A0 (en) * 1997-08-29 1997-09-25 Canon Kabushiki Kaisha Utilisation of caching in image manipulation and creation
US6816618B1 (en) * 1998-03-03 2004-11-09 Minolta Co., Ltd. Adaptive variable length image coding apparatus
US6130676A (en) * 1998-04-02 2000-10-10 Avid Technology, Inc. Image composition system and process using layers
US6081624A (en) * 1998-06-01 2000-06-27 Autodesk, Inc. Spatial index compression through spatial subdivision encoding
US6446109B2 (en) 1998-06-29 2002-09-03 Sun Microsystems, Inc. Application computing environment
US20020177911A1 (en) * 1998-09-30 2002-11-28 Lawrence Waugh Method and apparatus for determining an arrangement of components
JP3648089B2 (en) * 1999-03-18 2005-05-18 富士通株式会社 Design system and recording medium
IT1311443B1 (en) * 1999-11-16 2002-03-12 St Microelectronics Srl METHOD OF CLASSIFICATION OF DIGITAL IMAGES ON THE BASIS OF THEIR CONTENT.
AU2001293690A1 (en) * 2000-10-06 2002-04-15 Generic Vision Aps Method and system for multi-dimensional segmentation
DE60237553D1 (en) 2001-01-22 2010-10-14 Hand Held Prod Inc Optical reader with partial frame operating mode
US7268924B2 (en) 2001-01-22 2007-09-11 Hand Held Products, Inc. Optical reader having reduced parameter determination delay
GB2377205B (en) * 2001-07-04 2004-09-08 Hewlett Packard Co Lenticular images
US6961803B1 (en) * 2001-08-08 2005-11-01 Pasternak Solutions Llc Sliced crossbar architecture with no inter-slice communication
US7249125B1 (en) * 2003-10-09 2007-07-24 Computer Associates Think, Inc. System and method for automatically determining modal value of non-numeric data
JP4493050B2 (en) * 2005-06-27 2010-06-30 パイオニア株式会社 Image analysis apparatus and image analysis method
US7539343B2 (en) * 2005-08-24 2009-05-26 Hewlett-Packard Development Company, L.P. Classifying regions defined within a digital image
US7609891B2 (en) * 2005-08-31 2009-10-27 Sony Corporation Evaluation of element distribution within a collection of images based on pixel scatterness
US7734575B1 (en) * 2005-11-16 2010-06-08 Amdocs Software Systems Limited System, method, and computer program product for scaleable data collection and audience feedback
US8037404B2 (en) * 2009-05-03 2011-10-11 International Business Machines Corporation Construction and analysis of markup language document representing computing architecture having computing elements
JP6252674B2 (en) 2014-05-14 2017-12-27 新日鐵住金株式会社 Continuous casting method for slabs
GB2528669B (en) * 2014-07-25 2017-05-24 Toshiba Res Europe Ltd Image Analysis Method
US10423693B2 (en) * 2014-09-15 2019-09-24 Autodesk, Inc. Parallel processing using a bottom up approach
US9704056B2 (en) * 2015-04-02 2017-07-11 Qualcomm Incorporated Computing hierarchical computations for computer vision calculations
WO2019005098A1 (en) 2017-06-30 2019-01-03 Go Logic Decision Time, Llc Methods and systems of assertional projective simulation
WO2019005175A1 (en) 2017-06-30 2019-01-03 Intel Corporation Magnetoelectric spin orbit logic with displacement charge

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4174514A (en) * 1976-11-15 1979-11-13 Environmental Research Institute Of Michigan Parallel partitioned serial neighborhood processors
US4224600A (en) * 1979-03-26 1980-09-23 The Perkin-Elmer Corporation Arrays for parallel pattern recognition
US4363104A (en) * 1980-09-22 1982-12-07 Hughes Aircraft Company Imaging system having multiple image copying and hierarchical busing
US4507726A (en) * 1982-01-26 1985-03-26 Hughes Aircraft Company Array processor architecture utilizing modular elemental processors
US4622632A (en) * 1982-08-18 1986-11-11 Board Of Regents, University Of Washington Data processing system having a pyramidal array of processors
US4601055A (en) * 1984-04-10 1986-07-15 The United States Of America As Represented By The Secretary Of Commerce Image processor
US4850027A (en) * 1985-07-26 1989-07-18 International Business Machines Corporation Configurable parallel pipeline image processing system
JPH0634236B2 (en) * 1985-11-02 1994-05-02 日本放送協会 Hierarchical information processing method
JPH0785248B2 (en) * 1986-03-14 1995-09-13 株式会社東芝 Data Isle System
US4809346A (en) * 1986-07-18 1989-02-28 Hughes Aircraft Company Computer vision architecture for iconic to symbolic transformation
US4860201A (en) * 1986-09-02 1989-08-22 The Trustees Of Columbia University In The City Of New York Binary tree parallel processor
US4802090A (en) * 1987-06-24 1989-01-31 General Electric Company Histogramming of pixel values on a distributed processing system
US5022091A (en) * 1990-02-28 1991-06-04 Hughes Aircraft Company Image processing technique
US5193125A (en) * 1990-06-08 1993-03-09 Xerox Corporation Local hierarchical processing focus shift within an image

Also Published As

Publication number Publication date
US5280547A (en) 1994-01-18
EP0460970A2 (en) 1991-12-11
CA2041922C (en) 1995-07-18
JPH04296985A (en) 1992-10-21
EP0460970A3 (en) 1994-04-27

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