• International Journal of Highway Engineering
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• v.4 no.2 s.12
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• pp.33-42
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• 2002

The cracks in the pavements result from drying shrinkage, temperature change, repeated traffic loadings and so on. The reduction of soil support, spatting and many local failures are caused by water and incompressible foreign materials infiltrated into the cracks. In order to reduce this kind of problems the crack width must be controlled and managed by the accurate measurement. The current method is a visual survey using a microscope, which requires traffic blocking. The purpose of this study is to find the best condition to measure accurate crack width using automated pavement condition survey equipment running at the similar speed as other vehicles. In this study pavement surfaces are filmed on an enlarged scale by the camera with a zoom lens, and then the proper focal distance is determined according to the crack width through a pilot survey. The conditions for measurement of the accurate crack width using the image processing technique are suggested by comparing crack widths surveyed using a microscope in the field with those computed by various factors in the image processing program, STADI-2. In conclusion, the camera with a focal distance of 75m could detect crack range of 0.5mm$\sim$1.2mm In width with an accuracy of 80% for CRCP. The camera with a focal distance of 12.5mm could detect crack range of 1.8mm$\sim$3.3mm in width with an accuracy of 90% for asphalt pavement.

• The Journal of Bigdata
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• v.1 no.1
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• pp.19-22
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• 2016

Many Studies have been actively conducted on the early diagnosis of the crop pest utilizing IT technology. The purpose of the paper is to discuss on the image processing method capable of detecting the crop leaf pest prematurely by analyzing the image of the leaf received from the camera sensor. This paper proposes an algorithm of diagnosing leaf infection by utilizing an improved K means clustering method. Leaf infection grouping test showed that the proposed algorithm illustrated a better performance in the qualitative evaluation.

• 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.