Surface blemish detection from passive imagery using learned fuzzy set concepts

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An image analysis method for real-time surface blemish detection using passive imagery and fuzzy set concepts is described. The method develops an internal knowledge representation for surface blemish characteristics on the basis of experience, thus facilitating autonomous learning based upon positive and negative exemplars. The method incorporates fuzzy set concepts in the learning subsystem and image segmentation algorithms, thereby mimicking human visual perception. This enables a generic solution for color image segmentation. This method has been applied in the development of ARIES (Autonomous Robotic Inspection Experimental System), designed to inspect DOE warehouse waste storage drums for rust. In this project, ... continued below

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7 p.

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Gurbuz, S.; Carver, A. & Schalkoff, R. December 1, 1997.

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Description

An image analysis method for real-time surface blemish detection using passive imagery and fuzzy set concepts is described. The method develops an internal knowledge representation for surface blemish characteristics on the basis of experience, thus facilitating autonomous learning based upon positive and negative exemplars. The method incorporates fuzzy set concepts in the learning subsystem and image segmentation algorithms, thereby mimicking human visual perception. This enables a generic solution for color image segmentation. This method has been applied in the development of ARIES (Autonomous Robotic Inspection Experimental System), designed to inspect DOE warehouse waste storage drums for rust. In this project, the ARIES vision system is used to acquire drum surface images under controlled conditions and subsequently perform visual inspection leading to the classification of the drum as acceptable or suspect.

Physical Description

7 p.

Notes

INIS; OSTI as DE98051220

Source

  • IEEE - Region 3 Southeastcon `97 conference, Blacksburg, VA (United States), 12-14 Apr 1997

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  • Other: DE98051220
  • Report No.: DOE/FETC/C--98/7304
  • Report No.: CONF-9704176--
  • Grant Number: AC21-92MC29115
  • Office of Scientific & Technical Information Report Number: 634182
  • Archival Resource Key: ark:/67531/metadc693715

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • December 1, 1997

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  • Aug. 14, 2015, 8:43 a.m.

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  • Nov. 10, 2015, 9:36 p.m.

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Gurbuz, S.; Carver, A. & Schalkoff, R. Surface blemish detection from passive imagery using learned fuzzy set concepts, article, December 1, 1997; United States. (digital.library.unt.edu/ark:/67531/metadc693715/: accessed November 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.