摘要
设计并实现了一种基于一阶径向畸变模型的摄像机标定方法。对方格标定模板图像进行预处理,缩小角点检测范围,对SUSAN算子的USAN面积域值进行快速自适应选取,提高了角点检测的速度和准确度。在考虑了一阶径向畸变的情况下,建立摄像机模型,利用匹配后的图像角点亚像素坐标,逐步求解了内外参数。结果表明,本方法具有较高的精度和良好的实时性。
Radial distortion model was applied to camera calibration, so a new approach for camera calibration was designed and realized. Corner detector was combined with pretreatment of pane calibration template images, and a fast adaptive selection was proposed for USAN area threshold on the basis of SUSAN operator. The speed and accuracy of SUSAN algorithm were improved. A camera model with radial distortion was established to ealeulate the intrinsic and extrinsic parameters with the sub-pixel coordinates of the corner suited. The experimental result demonstrates high accuracy and efficiency of this approach.
出处
《东北林业大学学报》
CAS
CSCD
北大核心
2007年第6期51-53,共3页
Journal of Northeast Forestry University
关键词
摄像机标定
角点检测
自适应
Camera calibration
Corner detection
Adaptiveness
