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Hardware centric machine vision for high precision measurement of reference structures in optical navigation
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University , 2012. , p. 78
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 77
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-16176Local ID: STCISBN: 978-91-87103-05-6 (print)OAI: oai:DiVA.org:miun-16176DiVA, id: diva2:524888
Supervisors
Available from: 2012-05-04 Created: 2012-05-04 Last updated: 2016-10-20Bibliographically approved
List of papers
1. Hardware Centric Machine Vision for High Precision Center of Gravity Calculation
Open this publication in new window or tab >>Hardware Centric Machine Vision for High Precision Center of Gravity Calculation
2010 (English)In: PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, 2010, p. 736-743Conference paper, Published paper (Refereed)
Abstract [en]

We present a hardware oriented method for real-time measurements of object’s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.

Series
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, ISSN 2070-3724 ; Vol 64
Keywords
Dynamic thresholding, segmentation, position measurement, sub-pixel precision, center of gravity
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-11804 (URN)
Conference
WASET Int. conference on Digital Image Processing ICDIP 2010, Rome
Projects
OptiPos - Optical position measurement in real-time for consumer products
Available from: 2010-07-01 Created: 2010-07-01 Last updated: 2016-09-22Bibliographically approved
2. Optimized Color Pair Selection for Label Design
Open this publication in new window or tab >>Optimized Color Pair Selection for Label Design
2011 (English)In: Proceedings Elmar - International Symposium Electronics in Marine, Zadar, Croatia: IEEE conference proceedings, 2011, p. 115-118Conference paper, Published paper (Refereed)
Abstract [en]

We present in this paper a technique for designing reference labels that can be used for optical navigation. We optimize the selection of foreground and background colors used for the printed reference labels. This optimization calibrates for individual color responses among printers and cameras such that the Signal to Noise Ratio (SNR) is maximized. Experiments show that we get slightly smaller SNR for the color labels compared to using a monochrome technique. However, the number of segmented image components is reduced significantly by as much as 78 percent. This reduction of number of image components will in turn reduce the memory storage requirement for the computing embedded system.

Place, publisher, year, edition, pages
Zadar, Croatia: IEEE conference proceedings, 2011
Keywords
Label, Recognition, Position Measurement, COG, Subpixel Precision, RGB, HSI, YCbCr
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14531 (URN)2-s2.0-80055085889 (Scopus ID)STC (Local ID)978-953-7044-12-1 (ISBN)STC (Archive number)STC (OAI)
Conference
53rd International Symposium ELMAR-2011; Zadar; 14 September 2011 through 16 September 2011
Projects
Optipos
Available from: 2011-09-26 Created: 2011-09-26 Last updated: 2016-10-19Bibliographically approved
3. Color Symbol Design and Its Classification for Optical Navigation
Open this publication in new window or tab >>Color Symbol Design and Its Classification for Optical Navigation
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We explored the color symbol design and its recognition in image as reference structure for optical navigation. A colors pair was first determined as foreground and background from HSI color palette and then a color symbol was designed as reference structure. The advantage of using this selected color symbol is a significant reduction, up to 97%, of segmented image components as compared to the grey scale image used. The reduction of segmented components in image will result in saving the hardware resources e.g. memory and processing power which are very important constraint for embedded platforms. A color symbol pattern was designed, comprising of three concentric circles with selected color pair. Inside the inner most circle is the Area Of Interest (AOI), the contents of AOI depends on the particular application. A hardware centric image analysis algorithm is developed for easy and robust recognition. Image components are identified after preprocessing, segmentation and labeling. The color symbol can be recognized at a classification step. Evaluating a variety of viewing angles and reading distances ranging from 30 to 150 degrees and from 1 to 10 meters gives a classification success rate of 72 percent of the positions.

Keywords
Reference symbol, SNR, Classification, Nearest-neighbors rule, COG, Recognition, Position Measurement, Robotic Navigation, Machine Vision
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-15200 (URN)
Projects
STCIndustriella IT-system
Available from: 2011-12-13 Created: 2011-12-13 Last updated: 2012-08-10Bibliographically approved

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