1. A new surface roughness measurement method based on a color distribution statistical matrix
- Author
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Enhui Lu, Huaian Yi, Jian Liu, Peng Ao, and Menghui Wang
- Subjects
0209 industrial biotechnology ,Brightness ,Materials science ,Color image ,business.industry ,Machine vision ,Applied Mathematics ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,Surface finish ,Condensed Matter Physics ,01 natural sciences ,010309 optics ,Matrix (mathematics) ,020901 industrial engineering & automation ,Optics ,0103 physical sciences ,Surface roughness ,Texture (crystalline) ,Electrical and Electronic Engineering ,Diffusion (business) ,business ,Instrumentation - Abstract
A ground surface roughness measurement method is proposed to address current problems in the use of machine vision technology to measure roughness: the calculations are complex, and the measurement process is largely affected by the light source. Based on the area of diffusion regions between the virtual images formed by a light source on ground surfaces with different roughness levels are different, a reference light source containing two base color is designed. Red and green color space-based color distribution statistical matrices, as well as corresponding overlap indices, are proposed. A relationship model between overlap index and roughness is constructed. The effect of light source brightness and texture direction on the relationship model is discussed based on the experimental data. The results demonstrate that the surface roughness measurement method, which is based on the overlap degree of the color image, has relatively high accuracy and a relatively wide measurement range and is, to a certain degree, robust to the brightness of the light source and the texture direction. The surface roughness measurement method has huge potential for engineering applications.
- Published
- 2017
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