Abstract
Laser lines emitted by the laser level are mostly detected manually and laser particle and optical effects also bring difficulties on measurement. In this paper, we design a detection system for the five-line laser level and propose a laser line measurement method based on ma- chine vision. Image processing is divided into two stages: in the first stage, we use random sample consensus (RANSAC) algorithm combined with Hough transform to fit the laser axis, which can get its position information. In the second stage, a laser edge extraction method based on conditional random fields (CRFs) is proposed, and the sub-pixel width of laser line is obtained by spline interpolation algorithm. The results confirm that the laser level detection method proposed in this paper can realize the corresponding detection precision and requirement.
This work is supported by Key Project of Science and Technology Commission of Shanghai Municipality under Grant No. 14JC1402200
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Wang, X., Wang, H., Yang, A., Fei, M., Shen, C. (2017). Detection Method of Laser Level Line Based on Machine Vision. In: Fei, M., Ma, S., Li, X., Sun, X., Jia, L., Su, Z. (eds) Advanced Computational Methods in Life System Modeling and Simulation. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-6370-1_48
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DOI: https://doi.org/10.1007/978-981-10-6370-1_48
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