为了提高点云匹配识别过程中的特征提取效率和匹配精度，提出一种结合点云纹理信息的快速点特征直方图描述子算法。首先基于快速点特征直方图描述子构建形状特征直方图，采用CIELab色彩空间和多种点对纹理属性度量构建纹理特征直方图，然后将两特征直方图连接获得结合点云纹理信息的快速点特征直方图描述子。运用公开点云数据集及实景点云数据进行验证，对该特征描述子与多个现有描述子展开特征匹配试验及点密度变化试验。试验结果表明：当采用CIE00色差作为点对纹理属性度量时描述子的综合性能最佳;且该算法具有良好的特征描述性能和匹配精度，特征提取效率和匹配效率高，在点云密度变化时具有较强的鲁棒性。

A fast point feature histogram descriptor algorithm combined with point cloud texture information is proposed to improve the feature extraction efficiency and matching accuracy in the point cloud matching and recognition process. Firstly, a shape feature histogram was constructed based on the fast point feature histogram descriptor and a texture feature histogram was constructed by using CIELab color space and multiple point-to-texture attribute metrics. Then the two feature histograms were connected to obtain a fast point feature histogram descriptor combined with point cloud texture information. The feature histogram descriptor was verified by using public point cloud data sets and real spot cloud data. and the feature matching test and point density change test were carried out for this feature descriptor and multiple existing descriptors. The test results show that the comprehensive performance of the descriptor is the best when the CIE00 color difference is used as the point-to-texture attribute metrics. The algorithm has a good feature description performance and high feature extraction efficiency and matching efficiency and it has strong robustness when the point cloud density changes.