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- W2979863476 abstract "This article focuses on embedded vision systems and their automation and intelligent technology research, such as illumination, focal length, and surface roughness analysis. In illuminance, YCbCr color space conversion is used to obtain the contrast of brightness, and it becomes the basis for judging the illuminance state. In the focal length, the frequency domain space conversion is used to perform the spectral convolution operation, and it becomes the basis for judging the focal length state. In the surface roughness, the result of the spectral convolution operation becomes the input of the fuzzy C-means clustering algorithm and helps the fuzzy inference system (2 input -1 output) to establish the membership function and rule base. From the inference results of the fuzzy inference system, it is known that the surface roughness can be divided into three categories to obtain an accuracy of 91.67 %, and only five data are misjudged. At the same time, we hope that the low-cost embedded vision system can help the industry upgrade." @default.
- W2979863476 created "2019-10-18" @default.
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- W2979863476 date "2019-08-01" @default.
- W2979863476 modified "2023-09-27" @default.
- W2979863476 title "Analysis of Metal Surface Roughness Considering Illuminance and Focal Length Factors via FIS-based Embedded Vision System" @default.
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- W2979863476 doi "https://doi.org/10.1109/icamechs.2019.8861657" @default.
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