摘要
针对空间多视点图像的特点,提出基于模糊匹配的多视点图像配准方法.该方法采用由粗到细的原则研究空间多视点图像间的配准.在图像分割的基础上,考虑到不同视点图像间信息的不确定性,选择具有鲁棒性的区域面积、主颜色和亮度二阶矩等作为连通区域描绘子,并对其模糊化.引入模糊蕴涵计算不同视点图像每个连通区域间的模糊匹配度,从而推理出连通区域间的最佳匹配.最后通过反馈修正连通区域间关键特征点的匹配关系,实现具有自适应性的不同视点图像间的精确配准.实验验证文中方法的有效性.
According to the characteristics of spatial multi-view images, a fuzzy matching based multi-view image registration method is proposed by the principle of coarse-to-fine. Based on image segmentation, the uncertainty of the information from multi-view images is taken into account. The robust regional features such as area, dominant hue and second order moments of brightness are regarded as descriptors of connected regions and then the connected regions are fuzzed. By introducing fuzzy implication, the matching degree between connected regions in multi-view images is calculated. Then, the best matching relation between connected regions is built via fuzzy reasoning. Finally, the feedback correction is used for matching relationship between feature points of connected regions. The adaptive accurate registration between multi-view images is achieved. Meanwhile, the validity of the proposed method is demonstrated through experiments.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2014年第10期879-886,共8页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.10771043)
内蒙古自治区自然科学基金项目(No.2012MS0931)资助
关键词
模糊相似度
模糊蕴含算子
连通区域特征
Fuzzy Similarity, Fuzzy Implication Operator, Feature of Connected Regions
