研究了一种适用于不同类型光条图像的光条中心提取方法。构建了光条的截面能量模型,分析了不同成像质量光条的截面能量组成,构建了高斯-洛伦兹分峰拟合模型;基于所构建模型,依次对光条图像进行灰度归一化、感兴趣区域提取、高斯-洛伦兹分峰拟合、去洛伦兹分量处理,利用灰度重心法提取出精确的光条中心。对比实验结果表明,本文方法对不同类型光条图像的提取具有适用性强、精确度高,但耗时长的特点;然而对强漫反射和镜面反射光条的提取耗时仅为当前效果最好Steger法的1/2。

A light stripe center extraction algorithm is proposed based on Gauss-Lorenz peak fitting, which is suitable for different types of light stripe images. The cross-sectional energy model of a light stripe is built and the cross-sectional energy compositions of light stripes with different image qualities are analyzed, thus the Gauss-Lorenz decomposition fitting model is constructed. Based on the constructed model, the successive gray normalization, extraction of regions of interest, Gauss-Lorenz decomposition peak fitting and removal of Lorentzian components are acted on the light stripe images. The accurate light stripe center can be extracted with the gray centroid method. The contrast experimental results show that the proposed method has the characteristics of high extraction accuracy, strong applicability, but long time-consumption for different types of light stripe images. However, if it is applied to strong diffuse reflection and specular reflection light stipes, its time consumption is only half of that of Steger algorithm with the best effect at present.