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Da Li

at Nankai Univ

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Proceedings Article | 29 December 2023 Paper

Smart measurement system based on deep learning for microstructured surfaces

Yongqiang Yang, Chi Fai Cheung, Da Li

Proceedings Volume 12976, 1297618 (2023) https://doi.org/10.1117/12.3009078

KEYWORDS: Deep learning, 3D metrology, Data modeling, 3D modeling, Information fusion, Convolution, Visualization, Point clouds, Metrology

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The microstructured surfaces are playing an important role in industry. Measuring these surfaces quickly and accurately can provide significant quantitative results for machining process. However, traditional measurement methods and systems cannot meet the requirements of high precision machining. Measured samples are often moved several times in order to achieve the desired result. To address these limitations, a smart measurement system based on deep learning algorithm is established. The whole measurement system is portable and can be employed in many works situation. This smart measurement can offer an effective way of capturing high resolution images. To enhance the accuracy and efficiency of data processing, a deep learning model is applied in this system. This model can be employed to generate disparity after the input of high-resolution images. After the information fusion of disparity and the depth, which is obtained from the depth estimation module, the microstructured surfaces can be reconstructed accurately. This system is inputted with the synthetic data and experimental results show that the measurement uncertainty could reach at a sub-micrometer level.

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