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A Fuzzy Reasoning Method for Multi-views Image Registration

机译:多视图图像配准的模糊推理方法

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—Image registration is the key of target measurement, pattern recognition and computer vision. In view of characteristics of images from spatial multi-views, the principle of coarse-to-fine is used to study the registration of multi-view images. Based on image segmentation, taking uncertainty of information from multiview images into consideration, we regard robust regional features including area, dominant hue, n-order geometric moments as descriptors of connected regions and then fuzzify the connected regions. By introducing fuzzy implication, matching degree between connected regions in multi-views images is calculated. Then the best matching relation between connected regions is built via fuzzy reasoning. Finally, the feedback correction is used to matching relationship between feature points of connected regions. Then the adaptive accurate registration between multi-view images is achieved. The validity of proposed method is demonstrated through experiments.
机译:- 贴图是目标测量,模式识别和计算机视觉的关键。鉴于空间多视图图像的特征,粗细到精细的原理用于研究多视图图像的登记。基于图像分割,考虑到多视图图像的信息不确定性,我们认为强大的区域特征,包括区域,主导色调,n阶几何时刻作为连接区域的描述符,然后模糊连接区域。通过引入模糊暗示,计算多视图图像中的连接区域之间的匹配程度。然后通过模糊推理构建了连接区域之间的最佳匹配关系。最后,反馈校正用于匹配连接区域的特征点之间的关系。然后实现多视图图像之间的自适应精确登记。通过实验证明了所提出的方法的有效性。

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