An Automated Image Processing System for Concrete Evaluation

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AlliedSignal Federal Manufacturing & Technologies (FM&T) was asked to perform a proof-of-concept study for the Missouri Highway and Transportation Department (MHTD), Research Division, in June 1997. The goal of this proof-of-concept study was to ascertain if automated scanning and imaging techniques might be applied effectively to the problem of concrete evaluation. In the current evaluation process, a concrete sample core is manually scanned under a microscope. Voids (or air spaces) within the concrete are then detected visually by a human operator by incrementing the sample under the cross-hairs of a microscope and by counting the number of "pixels" which fall ... continued below

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Baumgart, C.W.; Cave, S.P. & Linder, K.E. November 23, 1998.

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Description

AlliedSignal Federal Manufacturing & Technologies (FM&T) was asked to perform a proof-of-concept study for the Missouri Highway and Transportation Department (MHTD), Research Division, in June 1997. The goal of this proof-of-concept study was to ascertain if automated scanning and imaging techniques might be applied effectively to the problem of concrete evaluation. In the current evaluation process, a concrete sample core is manually scanned under a microscope. Voids (or air spaces) within the concrete are then detected visually by a human operator by incrementing the sample under the cross-hairs of a microscope and by counting the number of "pixels" which fall within a void. Automation of the scanning and image analysis processes is desired to improve the speed of the scanning process, to improve evaluation consistency, and to reduce operator fatigue. An initial, proof-of-concept image analysis approach was successfully developed and demonstrated using acquired black and white imagery of concrete samples. In this paper, the automated scanning and image capture system currently under development will be described and the image processing approach developed for the proof-of-concept study will be demonstrated. A development update and plans for future enhancements are also presented.

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  • ANNIE '98 (Artificial Neural Networks in Engineering), St. Louis, MO, 11/1/98

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  • Other: DE00001881
  • Report No.: KCP-613-6111
  • Grant Number: NONE
  • Office of Scientific & Technical Information Report Number: 1881
  • Archival Resource Key: ark:/67531/metadc669203

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Office of Scientific & Technical Information Technical Reports

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  • November 23, 1998

Added to The UNT Digital Library

  • June 29, 2015, 9:42 p.m.

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  • Dec. 9, 2016, 3:28 p.m.

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Baumgart, C.W.; Cave, S.P. & Linder, K.E. An Automated Image Processing System for Concrete Evaluation, article, November 23, 1998; United States. (digital.library.unt.edu/ark:/67531/metadc669203/: accessed October 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.