摘要
针对现有亚像素边缘定位算法存在精度不高、计算复杂的问题,提出一种基于高斯积分曲面拟合的亚像素边缘定位算法。根据单边阶跃状边缘特征,构建边缘法截线的高斯积分模型,在确定边缘过渡带的基础上,将拟合曲面区域内的像素点信息转化为边缘曲线的活动坐标,并对转化后的像素点坐标与灰度值按照高斯积分模型进行拟合,准确定位图像的亚像素边缘。采用所述视觉测量系统,用量块直线边缘进行实验,并与传统高斯曲面拟合亚像素边缘定位算法比较,证明基于高斯积分曲面拟合的亚像素边缘定位算法具有较高的定位精度,一等量块的直线度误差在1μm以内,计算速度提高一倍。采用该算法确定亚像素边缘时,可通过修正高斯积分模型的均值,有效补偿光源强度造成的误差。本算法可以应用于齿轮等高精度机械零件的测量。
Aiming at the problems of low accuracy and complex calculation in existing sub-pixel edge location algorithm,a sub-pixel edge location algorithm is proposed based on Gauss integral curved surface fitting. According to the characteristic of unilateral step edge,the edge normal section line Gauss integral model is constructed,on the basis of determining edge transition zone,the pixel information in fitting curved surface area is transformed into the active coordinates of edge curve,and the transformed pixel coordinates and gray information are fitted according to Gauss integral model,the accurate sub-pixel edge of the image is located. With the vision measurement system described in this paper,the experiment on the gauge block line edge was conducted,and the result was compared with that for traditional Gauss curved surface fitting sub-pixel edge location algorithm. The result proves that the sub-pixel edge location algorithm based on Gauss integral curved surface fitting has high location accuracy,the linear error of the first grade gauge block is within1 μm,and the computing speed is doubled. When the algorithm is adopted to locate sub-pixel edge,the error caused by light source intensity can be effectively compensated through modifying the average of the Gauss integral model. Therefore,this algorithm can be applied to the high accurate measurement of mechanical parts,such as gears and etc.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2017年第1期219-225,共7页
Chinese Journal of Scientific Instrument
基金
国家科技支撑计划(2014BAF08B01)项目资助
关键词
视觉测量
法截线
过渡带
高斯积分
亚像素
vision measurement
normal section line
transition zone
Gauss integral
sub-pixel
