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刘帅, 赵伶俐, 陈军, 孙敏, 郭红伟, 韦相. 球形全景核线约束的颜色不变量综合特征快速匹配方法[J]. 计算机辅助设计与图形学学报, 2023, 35(4): 589-598. DOI: 10.3724/SP.J.1089.2023.19385
引用本文: 刘帅, 赵伶俐, 陈军, 孙敏, 郭红伟, 韦相. 球形全景核线约束的颜色不变量综合特征快速匹配方法[J]. 计算机辅助设计与图形学学报, 2023, 35(4): 589-598. DOI: 10.3724/SP.J.1089.2023.19385
Liu Shuai, Zhao Lingli, Chen Jun, Sun Min, Guo Hongwei, and Wei Xiang. Fast Matching Method of Color Invariant Synthetic Features Constrained by Spherical Panoramic Epipolar Lines[J]. Journal of Computer-Aided Design & Computer Graphics, 2023, 35(4): 589-598. DOI: 10.3724/SP.J.1089.2023.19385
Citation: Liu Shuai, Zhao Lingli, Chen Jun, Sun Min, Guo Hongwei, and Wei Xiang. Fast Matching Method of Color Invariant Synthetic Features Constrained by Spherical Panoramic Epipolar Lines[J]. Journal of Computer-Aided Design & Computer Graphics, 2023, 35(4): 589-598. DOI: 10.3724/SP.J.1089.2023.19385

球形全景核线约束的颜色不变量综合特征快速匹配方法

Fast Matching Method of Color Invariant Synthetic Features Constrained by Spherical Panoramic Epipolar Lines

  • 摘要: 针对目前立体全景模型量测应用中特征匹配自动化程度偏低的问题,提出一种基于立体球形全景约束的颜色不变量综合特征快速匹配方法.首先,通过核线约束,使全景影像匹配的搜索范围从二维限制到一维带状缓冲区域;然后利用颜色不变量相关系数进一步确定精细搜索范围;最后,基于颜色不变量及旋转不变纹理特征构建综合匹配测度模型,以实现全景特征匹配.通过实地拍摄的全景图像,与灰度匹配法、SIFT,SURF以及CSIFT进行比较分析.实验结果表明,该方法匹配准确率提高了近10%,可消减球形全景特征的误匹配,有效地解决影像匹配时同名像点自动寻找与几何信息快速解算,为全景量测模型二次采样、量测及深度图的生成奠定基础.

     

    Abstract: To address the problem of low automation of feature matching in stereo panoramic model measurement applications, a color invariant synthetic feature matching method based on epipolar geometric constraints is proposed. Firstly, the method limits the search range of panoramic image matching from two-dimensional to one-dimensional band buffer by epipolar line constraint. Secondly, the method uses the color invariant correlation coefficient to further determine the fine search range. Finally, the method establishes a kind of matching synthetic measure model to complete panoramic feature matching based on color invariant feature and the rotation invariant local binary patterns. After taking panoramic images in the field and feature matching nearly 200 groups of points, the matching accuracy of the method proposed in this paper is improved by nearly 10% compared with the gray-scale matching method, SIFT, SURF and CSIFT. The matching error of the proposed method can be decrease greatly, and the reliability and precision of spherical panorama image matching is effectively improved, which can lay the foundation for secondary sampling, measurement and depth map generation of panoramic measurement model.

     

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