连接向量特征匹配的暗场图像配准方法

利用损伤点之间的位置关系，根据光学元件损伤暗场图像的特点设计了一种基于连接向量特征匹配的配准方法。该方法首先对基准图像及待配准图像分别进行图像预处理，提取损伤点轮廓的中心坐标作为损伤点的位置值。然后构建损伤点连接向量，求出主方向并计算主方向下的连接向量特征，使用连接向量匹配获得匹配点对，最后利用RANSAC算法对匹配点对进行仿射变换参数计算。该方法具有旋转不变性，尺度不变性以及较高的配准准确度。实验对比分析了该方法与SIFT算法的计算效率及配准精度，结果表明在暗场图像条件下文中方法更有效且为背景单一，灰度信息较少同时要求较高的配准速度的场景下的图像配准问题提供了解决方案。

Dark field image registration based on connection vector feature matching method

Based on the the positional relationship between damage points and characteristics of optical damage dark field image, a registration method using connection vector feature matching was designed. The method firstly preprocessed the reference image and the image to be registered, and then extracted the center coordinates of the contour of the damage point as the position value of the damage point. Then the connection vector of the damage points was constructed, the main direction was obtained and the connection vector feature in the main direction was calculated, the exact match was achieved through the fine matches. Finally, the affine transformation parameter was calculated by using the RANSAC algorithm. The method had rotational invariance, scale invariance and high registration accuracy. The computational efficiency and registration precision of this method and SIFT algorithm were compared and analyzed. The experimental results show the more effectiveness of the proposed method in dark field image.