基于仿射变换和均值像素法的环状编码点鲁棒识别

在近景工业摄影测量中,针对环状编码点精确定位和准确识别的要求,提出了一种鲁棒性识别算法。该算法在对目标图像预处理后,首先根据边缘滤波准则初步定位编码点,并将含编码带的特征区域分割出来。然后,利用最小二乘法对特征区域进行仿射变换,将经透视投影退化的椭圆映射成规则圆形。最后,采用均值像素法获取环状编码点的解码值,进一步提高编码点的抗噪性。大量实验结果表明:该方法在对编码点的中心定位达到亚像素级别的同时,改善了算法对识别角度的鲁棒性,在识别角度为70°时,正确识别率仍可达97.9%,在实际复杂场景中具有较好的实用价值。

Robust recognition of circular coded point based on affinetransformation and average pixel method

In close range industrial photogrammetry, according to the requirements of precise positioning and accurate recognition ofcircular coded point, a robust recognition algorithm is proposed. After preprocessing the target image, the algorithm firstly locates thecoded point initially according to the edge filtering criterion and segment the feature region containing coding band. Then, the leastsquare method is used to perform affine transformation on the feature region and the degenerated ellipse in perspective projection ismapped into a regular circle. Finally, the average pixel method is used to obtain the decoding value of the circular coded points, whichfurther improves the anti-noise performance of the circular coded points. A large number of experiment results show that this method cannot only achieve sub-pixel level in the center location of circular coded points, but also improve the robustness to the recognition angle ofthe algorithm. When the recognition angle is 70°, the correct recognition rate can still reach 97. 9% , which has good practicalapplication value in actual complex scene.