近景摄影测量中标记点的自动检测

近景摄影测量中，可以在待测物体表面分布一些易于识别的标记点，以提高特征识别的准确性和精度，保证多幅图象间特征点对应匹配的可靠性。文中采用圆形目标及编码元素作为标记点，并提出一种标记点自动检测算法。该算法首先根据标记点的尺寸、形状、灰度变化及位置分布等特征提取目标；然后利用非编码元与编码元的不同形状与灰度特征，提出一种改进的编码元自动身份识别方法，同时实现非编码元与编码元的分类；最后采用质心法进行标记点的精确定位，达到亚象素精度。实验结果表明，该方法受投影角度、噪声等因素影响小，具有很强的鲁棒性，可以实现标记点的准确识别和精确定位，实用性好。

Automated Reference Point Detection in Close Range Photogrammetry

Distributing reference points on the object to be measured is a reliable and common method for achieving optimum target location and accurate correspondence among multi-view images.In this paper circular uncoded targets and coded targets are used as reference points,and an algorithm of automatic reference point detection is proposed.Targets are extracted from the images according to their size,shape,intensity,etc.An improved method to identify every coded target is proposed.The gray scale centroid algorithm is applied to get subpixel locations of both uncoded and coded targets.Practical examples show that the algorithm can identify and locate reference points accurately.It is robust to the change of projection angles and noise.