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A platform for research: civil engineering, architecture and urbanism
Mastercurve-based image analysis method for curing compound quality control
Abstract Curing compounds are widely used to cure concrete pavement because of their high efficiency and simple usability. Image processing has been proposed to facilitate quality control during construction by including a white-colored pigment in the sprayed compound. However, errors can occur as a result of a number of variables such as camera aperture, shutter speed, and illuminance during the picture-taking process. This paper proposes a method in which the “mastercurve” concept is applied to standardize the camera aperture and shutter speed. The shift function, y = 0.0067x2 − 0.2305x + 1.4171, is applied between the aperture and shutter speed, and a brightness value enabled to classify curing compounds under the same illuminance condition. In addition, the correlation between the illuminance and brightness of the images are identified via regression analysis. The results of analysis of sample images under various conditions indicate that the relative application rate of the curing compound can be evaluated. These results demonstrate that the proposed image processing methodology is suitable for curing compound quality control.
Mastercurve-based image analysis method for curing compound quality control
Abstract Curing compounds are widely used to cure concrete pavement because of their high efficiency and simple usability. Image processing has been proposed to facilitate quality control during construction by including a white-colored pigment in the sprayed compound. However, errors can occur as a result of a number of variables such as camera aperture, shutter speed, and illuminance during the picture-taking process. This paper proposes a method in which the “mastercurve” concept is applied to standardize the camera aperture and shutter speed. The shift function, y = 0.0067x2 − 0.2305x + 1.4171, is applied between the aperture and shutter speed, and a brightness value enabled to classify curing compounds under the same illuminance condition. In addition, the correlation between the illuminance and brightness of the images are identified via regression analysis. The results of analysis of sample images under various conditions indicate that the relative application rate of the curing compound can be evaluated. These results demonstrate that the proposed image processing methodology is suitable for curing compound quality control.
Mastercurve-based image analysis method for curing compound quality control
Jung, YooSeok (author) / Lee, Jae Hoon (author) / Mun, Nam Sik (author) / Cho, Yoon-Ho (author)
KSCE Journal of Civil Engineering ; 21 ; 253-257
2016-03-04
5 pages
Article (Journal)
Electronic Resource
English
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