A Robust Method for Adaptive Center Extraction of Linear Structured Light Stripe

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 greyvalue 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.

Sub-pixel extraction of laser stripeand itsapplication in laser plane calibration

For calibrating the laser plane to implement 3D shape measurement, an algorithm for extracting the laser stripe with sub-pixel accuracy is proposed. The proposed algorithm mainly consists of two stages： two-side edge detection and center line extraction. First, the two-side edge of laser stripe is detected using the principal component angle-based progressive probabilistic Hough transform and its width is calculated through the distance between these two edges. Secondly, the center line of laser strip is extracted with 2D Taylor expansion at a sub-pixel level and the laser plane is calibrated with the 3D reconstructed coordinates from the extracted 2D sub-pixel ones. Experimental results demonstrate that the proposed method can not only extract the laser stripe at a high speed, nearly average 78 ms/frame, but also calibrate the coplanar laser stripes at a low error, limited to 0.3 mm. The proposed algorithm can satisfy the system requirement of two-side edge detection and center line extraction, and rapid speed, high precision, as well as strong anti-jamming.

Method for Detecting Weld Feature Size Based on Line Structured Light

With the rapid development of the machining and manufacturing industry,welding has been widely used in forming connections of structural parts.At present,manual methods are often used for welding and quality inspection,with low efficiency and unstable product quality.Due to the requirements of visual inspection of weld feature size,a visual inspection system for weld feature size based on line structured light(LSL)is designed and built in this paper.An adaptive light stripe sub-pixel center extraction algorithm and a feature point extraction algorithm for welding light stripe are proposed.The experiment results show that the detection error of the weld width is 0.216 mm,the detection error of the remaining height is 0.035 mm,the single measurement costs 109 ms,and the inspection stability and repeatability of the system is 1%.Our approach can meet the online detection requirements of practical applications.