A Robust Method for Adaptive Center Extraction of Linear Structured Light Stripe
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Abstract:
In the non-contact measurement using the linear structured light (LSL), the extraction precision of the light stripe center directly affects the measurement accuracy of the whole detection system. To solve the problem that general algorithms cannot accurately extract the center of the light stripe with the uneven width and unstable grey-value distribution, an adaptive optimization method is proposed. In this method, the stripe region is firstly segmented, and the widths of the laser stripe are calculated by boundary detection. The initial stripe center points are computed by the quadratic weighted grayscale centroid method based on the self-adaptive stripe width. After that, these center points are optimized according to the determined slope threshold. The sub-pixel coordinates of these center points are recalculated. Detailed analysis is also performed in line with the proposed evaluation index of the extraction algorithm. The experimental results show that the mean square error of extracted center points is only 0.1 pixel, meaning that the accuracy of laser stripe center extraction is improved significantly by the method. Furthermore, the method can run effectively at a relatively low computational time cost, and can demonstrate great robustness as well.
LU Yonghua, ZHANG Jia, LI Xiaoyan, LI Yanlong, TAN Jie. A Robust Method for Adaptive Center Extraction of Linear Structured Light Stripe[J]. Transactions of Nanjing University of Aeronautics & Astronautics,2020,37(4):586-596