SE0102254L - Digital image processing - Google Patents

Digital image processing

Info

Publication number
SE0102254L
SE0102254L SE0102254A SE0102254A SE0102254L SE 0102254 L SE0102254 L SE 0102254L SE 0102254 A SE0102254 A SE 0102254A SE 0102254 A SE0102254 A SE 0102254A SE 0102254 L SE0102254 L SE 0102254L
Authority
SE
Sweden
Prior art keywords
digital image
threshold
subarea
basis
calculation unit
Prior art date
Application number
SE0102254A
Other languages
Swedish (sv)
Other versions
SE0102254D0 (en
Inventor
Andreas Olsson
Original Assignee
Anoto Ab
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 Anoto Ab filed Critical Anoto Ab
Priority to SE0102254A priority Critical patent/SE0102254L/en
Publication of SE0102254D0 publication Critical patent/SE0102254D0/en
Priority to EP02741593A priority patent/EP1421555A1/en
Priority to PCT/SE2002/001244 priority patent/WO2003001450A1/en
Priority to US10/179,967 priority patent/US7110604B2/en
Publication of SE0102254L publication Critical patent/SE0102254L/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition
    • G06V30/14—Image acquisition
    • G06V30/142—Image acquisition using hand-held instruments; Constructional details of the instruments
    • G06V30/1423—Image acquisition using hand-held instruments; Constructional details of the instruments the instrument generating sequences of position coordinates corresponding to handwriting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10048—Infrared image

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

In a method for identifying individual objects in a digital image (I), a device is used that comprises a theresholding unit (20) and a threshold calculation unit (21). the thresholding unit (20) is designed to receive the digital image (I) and compare the luminance values of the digital image with threshold values (Ti) of a threshold matrix (T) in order to create a binary image on the basis of the comparison. The threshold calculation unit (21) is designed to estimate, on the basis of a first and second division of a reference image which corresponds to the digital image (I) into first and second subareas, a background luminance value for each first subarea and an object luminance value for each second subarea. For each overlapping first and second subarea, the threshold calculation unit (21) calculates a threshold value (Ti) on the basis on the associated background and object luminancevalues, and creates the threshold matrix (T) from said threshold values (Ti). The device and the method permit quick and memory-efficient identification of the individual objects, even if the digital image (I) contains variations in luminance and/or sharpness. A computer program product, a hardware circuit and a hand-held apparatus for position determination are also described.
SE0102254A 2001-06-26 2001-06-26 Digital image processing SE0102254L (en)

Priority Applications (4)

Application Number Priority Date Filing Date Title
SE0102254A SE0102254L (en) 2001-06-26 2001-06-26 Digital image processing
EP02741593A EP1421555A1 (en) 2001-06-26 2002-06-25 Processing of digital images
PCT/SE2002/001244 WO2003001450A1 (en) 2001-06-26 2002-06-25 Processing of digital images
US10/179,967 US7110604B2 (en) 2001-06-26 2002-06-26 Processing of digital images

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
SE0102254A SE0102254L (en) 2001-06-26 2001-06-26 Digital image processing

Publications (2)

Publication Number Publication Date
SE0102254D0 SE0102254D0 (en) 2001-06-26
SE0102254L true SE0102254L (en) 2002-12-27

Family

ID=20284605

Family Applications (1)

Application Number Title Priority Date Filing Date
SE0102254A SE0102254L (en) 2001-06-26 2001-06-26 Digital image processing

Country Status (3)

Country Link
EP (1) EP1421555A1 (en)
SE (1) SE0102254L (en)
WO (1) WO2003001450A1 (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7457476B2 (en) 2001-10-03 2008-11-25 Anoto Ab Optical sensor device and a method of controlling its exposure time
WO2008002239A1 (en) 2006-06-28 2008-01-03 Anoto Ab Operation control and data processing in an electronic pen
EP2064658A4 (en) 2006-09-07 2017-08-23 Lumex As Relative threshold and use of edges in optical character recognition process
CN116629289A (en) * 2023-05-23 2023-08-22 深圳市牛加技术有限公司 Optical lattice two-dimensional coordinate recognition method and device based on convolutional neural network

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4593325A (en) 1984-08-20 1986-06-03 The Mead Corporation Adaptive threshold document duplication
US5051736A (en) 1989-06-28 1991-09-24 International Business Machines Corporation Optical stylus and passive digitizing tablet data input system
US5477012A (en) 1992-04-03 1995-12-19 Sekendur; Oral F. Optical position determination
US5852434A (en) 1992-04-03 1998-12-22 Sekendur; Oral F. Absolute optical position determination
US5661506A (en) 1994-11-10 1997-08-26 Sia Technology Corporation Pen and paper information recording system using an imaging pen
US5629780A (en) * 1994-12-19 1997-05-13 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Image data compression having minimum perceptual error
US5963676A (en) * 1997-02-07 1999-10-05 Siemens Corporate Research, Inc. Multiscale adaptive system for enhancement of an image in X-ray angiography
FR2786011B1 (en) * 1998-11-13 2001-01-19 Centre Nat Etd Spatiales METHOD OF COMPARISON OF RECORDED IMAGES SHAPED OF PIXELS REPRESENTING EQUIPOTENTIALS OF AT LEAST ONE INTEGRATED CIRCUIT CHIP
ATE469390T1 (en) 1999-05-28 2010-06-15 Anoto Ab POSITION DETERMINATION

Also Published As

Publication number Publication date
SE0102254D0 (en) 2001-06-26
EP1421555A1 (en) 2004-05-26
WO2003001450A1 (en) 2003-01-03

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