• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.2
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• pp.148-156
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• 2007

The fiber dispersion in fiber-reinferced cementitious composites is a crucial factor with respect to achieving desired mechanical performance. However, evaluation of the fiber dispersion in the composite PVA-ECC (polyvinyl alcohol-engineered cementitious composite) is extremely challenging because of the low contrast of PVA fibers with the cement-based matrix. In the present work, a new evaluation method is developed and demonstrated. Using a fluorescence technique on the PVA-ECC, PVA fibers are observed as green dots in the cross-section of the composite. After capturing the fluorescence image with a charged couple device (CCD) camera through a microscope, the fiber dispersion is evaluated using an image processing technique and statistical tools. In this image processing technique, the fibers are more accurately detected by employing an enhanced algorithm developed based on a discriminant method and watershed segmentation. The influence of fiber orientation on the fiber dispersion evaluation was also investigated via shape analyses of fiber images.

• Proceedings of the Korean Fiber Society Conference
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• 1999.10a
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• pp.179-182
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• 1999

• 발명특허
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• v.31 no.12 s.365
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• pp.41-42
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• 2006

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2010.10a
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• pp.59-60
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• 2010

• Geotechnical Engineering
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• v.28 no.11
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• pp.35-37
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• 2012

• Fiber Technology and Industry
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• v.5 no.1_2
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• pp.10-15
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• 2001

• Construction Engineering and Management
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• v.23 no.5
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• pp.16-20
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• 2022

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.281-282
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• 2012

Construction performance and productivity improvement are key focus areas in construction industry for any nation. There have been frequent delays and cost overruns in construction projects and poor productivity is one of the major contributions. For this reasons, there have been many research studies performed on the improvement of construction productivity for several decades. However, measuring productivity on a construction job site is still not an easy work. Because collecting reliable data consistently from the job site requires a lot of personnel efforts causing extra time and cost. This paper provides a basic study on the application of image processing technology for measuring unit productivity. It presented the possibility of unit productivity measurement by image processing technology through case study.

• Journal of the Korean Society of Visualization
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• v.2 no.1
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• pp.25-31
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• 2004

Droplet size is one of the most important parameter which controls the performance of the combustion system using liquid fuel or oxidizer. Droplet formation and its size are mainly affected by the injection velocity and ambient gas density. Recently, droplet size measurement was conducted by PDPA or Malvern particle analyzer using laser light. But at this paper image processing method was developed to measure droplet size. And its validation was investigated with reticle.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2768-2770
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• 2001

본 논문은 지능형 알고리즘과 이미지 프로세싱 방법을 결합한 새로운 방법으로 칼라 매칭 시스템에 구현한다. 칼라 매칭 시스템은 이미지 프로세싱을 이용하여 칼라의 RGB 데이터를 분석한 후 얻어진 색상정보를 가지고 사용자가 원하는 칼라는 구현하는 시스템이다. 칼라 매칭 시스템의 모델링에 이용되는 지능형 모델은 퍼지 추론과 적응 퍼지 추론 시스템(Adaptive Neuro-Fuzzy Inference System: ANFIS)이며, 최소 자승법을 기반으로 한 회귀 다항식과 비교하여 제안된 지능형 모델에 대한 성능과 실용성을 검증한 후 델파이를 이용하여 구현하였다.