Sub-pixel extraction of laser stripe in complex background

Abstract

The complex background and laser stripe noise affect laser stripe extraction. Adaptive double threshold segmentation method and the improved gray weight model are proposed in this study. First, the characteristics of the laser stripe and the source of noise in the image are investigated. Bilateral filter is applied to remove the noise of images. Subsequently, the gray histogram of laser image and the double threshold are computed. By sub-regional processing, initial stripe center and stripe width of binary images are obtained. Finally, the sub-pixel center of the laser strip is extracted by the proposed model. The double threshold segmentation method and the improved gray weight model are compared with the traditional algorithms. The results show that the double threshold method is more accuracy in extracting the laser stripe region than the extreme value method and the Otsu method. Comparing with the residual value of sub-pixel center, the improved gray weight model (0.23) has better results than the gray-gravity method (0.71), the extreme value method (0.86), and the Gaussian fitting method (0.86). The algorithms proposed in this study avoid the impacts of complex background and laser stripe noise, increase the accuracy of the laser stripe center positioning and extract the stripe center extraction fast and accurately in complex backgrounds.