基于骨架邻近像素匹配的光条中心提取方法

doi:10.12068/j.issn.1005-3026.2023.11.002

摘要/Abstract

摘要： 提出一种基于骨架邻近像素匹配的线结构光条中心提取方法，分别在图像预处理阶段和光条中心提取阶段对传统方法进行改进.在图像预处理阶段，将马尔可夫随机场理论应用于二值图像去噪中，同时提出了一种基于连通域面积特性的ROI(region of interest)提取方法.在光条中心提取阶段，首先提出了一种光条骨架剪枝算法，对细化ROI得到的光条骨架进行剪枝、平滑，之后综合考虑光条图像的几何特性和灰度分布特性，基于邻近分析对ROI内各像素进行划分，继而求取出灰度重心，最后经Savitzky-Golay滤波后实现光条中心提取.实验结果表明，所提方法对不同类型光条的提取适用性强，相较于Steger法精度更高，且速度在其基础上提高了约6.98倍.

关键词: 图像处理；线结构光；光条中心提取；骨架细化；灰度重心法

Abstract: An method of the line-structured light stripe center extraction based on the matching of adjacent pixels of skeleton is proposed. The traditional method is improved in the phase of image preprocessing and light stripe center extraction. In the phase of image preprocessing， Markov’s random field theory is applied to denoise binary images， and a method of extracting region of interest(ROI)based on the area characteristics of connected regions is proposed. In the phase of light stripe center extraction， firstly， a light stripe skeleton pruning method is proposed to prune and smooth the stripe skeleton obtained by the refined ROI. Secondly， considering the geometric and gray distribution characteristics of the light stripe image， the pixels in the ROI are divided based on an analysis of adjacent areas， and then the gray barycenter is obtained. Finally， Savitzky-Golay filter is used to extract the center of light stripe with sub-pixel precision. Experimental results show that the proposed method has strong applicability for different types of light stripe extraction and achieves higher precision compared with Steger method. And it’s worth noting that the speed of the proposed method is about 6.98 times higher than that of the Steger method.

Key words: image processing; line-structured light; light stripe center extraction; skeleton refinement; gray-barycenter method

中图分类号:

TP391

张铫，夏雨风，王梓琦，刘洋. 基于骨架邻近像素匹配的光条中心提取方法[J]. 东北大学学报（自然科学版）, 2023, 44(11): 1529-1536.

ZHANG Yao， XIA Yu-feng， WANG Zi-qi， LIU Yang. Extraction Method of Light Stripe Center Based on the Matching of Adjacent Pixels of Skeleton[J]. Journal of Northeastern University(Natural Science), 2023, 44(11): 1529-1536.

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