像素
RGB颜色模型
强度(物理)
灰度
计算机视觉
图像(数学)
人工智能
数学形态学
材料科学
图像处理
光学
计算机科学
物理
作者
Yuriy Vashpanov,Jung‐Young Son,Gwanghee Heo,Tatyana Podousova,Yong‐Suk Kim
出处
期刊:Book Publisher International (a part of SCIENCEDOMAIN International)
[Book Publisher International (a part of SCIENCEDOMAIN International)]
日期:2021-05-19
卷期号:: 41-58
标识
DOI:10.9734/bpi/aaer/v11/8268d
摘要
The 8-bit RGB image of a cracked concrete surface, obtained with a high resolution camera based on a close distance photographing and using an optical microscope is used to estimate the geometrical parameters of the crack. The parameters such as the crack’s width, depth and morphology can be determined by the pixel intensity distribution of the image. For the estimation, the image is transformed into 16-bit gray scale to enhance the geometrical parameters of the crack and then. a mathematical relationship relating the intensity distribution with the depth and width is derived based on the enhanced image. This relationship enables to estimate the width and depth with ±10% and ±15% accuracy, respectively for the crack samples used for the experiments. OriginLab tools were used for mathematical processing of image data and statistical calculations of geometric parameters of cracks in concrete. It is expected that the accuracy can be further improved if the 8-bit RGB image is synthesized by the images of the cracks obtained with different illumination directions.
科研通智能强力驱动
Strongly Powered by AbleSci AI