An intelligent system for analyzing welding defects using image retrieval techniques

Raoul P. Pein; Joan Lu; John B. Stav; Qiang Xu; Miro Uran; Luboš Mráz

An intelligent system for analyzing welding defects using image retrieval techniques

Raoul P. Pein, Joan Lu, John B. Stav, Qiang Xu, Miro Uran, Luboš Mráz

Research output: Contribution to conference › Paper › peer-review

Abstract

The development of new approaches in image processing and retrieval provides several opportunities in supporting in different domains. The group of welding engineers frequently needs to conduct visual inspections to assess the quality of welding products. It is investigated, if this process can be supported by different kinds of software. Techniques from a generic CBIR system have been successfully used to cluster welding photographs according to the severeness of visual faults. Similarity algorithms were used to automatically spot faults, such as cracks and gas pores.

Original language	English
Pages	919-924
Publication status	Published - 2009
Externally published	Yes
Event	19th International Conference on Flexible Automation and Intelligent Manufacturing - Teesside University, Middlesbrough, United Kingdom Duration: 6 Jul 2009 → 8 Jul 2009 Conference number: 19

Conference

Conference	19th International Conference on Flexible Automation and Intelligent Manufacturing
Abbreviated title	FAIM 2009
Country/Territory	United Kingdom
City	Middlesbrough
Period	6/07/09 → 8/07/09

Cite this

@conference{ed9963544cf2497798400affeda643b3,

title = "An intelligent system for analyzing welding defects using image retrieval techniques",

abstract = "The development of new approaches in image processing and retrieval provides several opportunities in supporting in different domains. The group of welding engineers frequently needs to conduct visual inspections to assess the quality of welding products. It is investigated, if this process can be supported by different kinds of software. Techniques from a generic CBIR system have been successfully used to cluster welding photographs according to the severeness of visual faults. Similarity algorithms were used to automatically spot faults, such as cracks and gas pores.",

author = "Pein, {Raoul P.} and Joan Lu and Stav, {John B.} and Qiang Xu and Miro Uran and Lubo{\v s} Mr{\'a}z",

year = "2009",

language = "English",

pages = "919--924",

note = "19th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2009 ; Conference date: 06-07-2009 Through 08-07-2009",

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TY - CONF

T1 - An intelligent system for analyzing welding defects using image retrieval techniques

AU - Pein, Raoul P.

AU - Lu, Joan

AU - Stav, John B.

AU - Xu, Qiang

AU - Uran, Miro

AU - Mráz, Luboš

N1 - Conference code: 19

PY - 2009

Y1 - 2009

N2 - The development of new approaches in image processing and retrieval provides several opportunities in supporting in different domains. The group of welding engineers frequently needs to conduct visual inspections to assess the quality of welding products. It is investigated, if this process can be supported by different kinds of software. Techniques from a generic CBIR system have been successfully used to cluster welding photographs according to the severeness of visual faults. Similarity algorithms were used to automatically spot faults, such as cracks and gas pores.

AB - The development of new approaches in image processing and retrieval provides several opportunities in supporting in different domains. The group of welding engineers frequently needs to conduct visual inspections to assess the quality of welding products. It is investigated, if this process can be supported by different kinds of software. Techniques from a generic CBIR system have been successfully used to cluster welding photographs according to the severeness of visual faults. Similarity algorithms were used to automatically spot faults, such as cracks and gas pores.

M3 - Paper

SP - 919

EP - 924

T2 - 19th International Conference on Flexible Automation and Intelligent Manufacturing

Y2 - 6 July 2009 through 8 July 2009

ER -

An intelligent system for analyzing welding defects using image retrieval techniques

Abstract

Conference

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