CAJ | 학술논문

高精度快速靶标点的自动提取是相机标定、立体解算、视觉导航等关键领域的基础。定位精度和算法稳健性为难点之所在，采用重心约束法检测初始交点后，通过对称性约束探测直线附近的“脊点”点集，然后采用最小二乘线性拟合初值并迭代滤掉粗差，再采用改进的Hough变换进一步求得交点的位置。然后采用惩罚函数在初始点附近步进调整，精确确定靶标点的位置信息和方向。算法能够更强地适应噪声环境下、光照变化、图像旋转等影响，达到小于0.05像素的定位精度。
고정도쾌속파표점적자동제취시상궤표정、입체해산、시각도항등관건영역적기출。정위정도화산법은건성위난점지소재，채용중심약속법검측초시교점후，통과대칭성약속탐측직선부근적“척점”점집，연후채용최소이승선성의합초치병질대려도조차，재채용개진적Hough변환진일보구득교점적위치。연후채용징벌함수재초시점부근보진조정，정학학정파표점적위치신식화방향。산법능구경강지괄응조성배경하、광조변화、도상선전등영향，체도소우0.05상소적정위정도。
Automatic marking points extracting with high accuracy is basic for calibration, stereo calculation, visual navigation and other applications. The bottle- neck is the accuracy and robustness. Based on the rough point from the cross of lines of the neighbor barycenters in two directions, the ridge points were detected by the symmetric function and refined by an iterative least square method, based on the refined ridge points, the Hough transform was improved for determining the lines and their intersections. At last, the position of the marking points was to be adjusted by the penalty function with a changing step along the descent direction both in deflection and rotation separately. Our algorithm is robust to noisy, rotation, illumination variations and a certain degree of distortions, the accuracy could be less than 5 percents of a pixel.