基于SUSAN和Hough变换的直线边缘亚像素定位方法

Method of Straight Edge Detection with Sub-pixel Localization Based on SUSAN and Hough Transform

提出了一种基于SUSAN算法和Hough变换的直线边缘亚像素定位方法。在该方法中,给出了SUSAN算法模板选择的依据,同时定义了直线边缘响应函数并引入加权Hough变换。首先,利用直线边缘响应函数对直线边缘进行提取;然后对具有响应值的灰度点进行Hough变换并将该响应值作为权值记入参数空间累加器,得到粗定位;在粗定位的基础上对映射区进行局部细化,并对区域内点进行拟合,最终得到直线边缘精定位。实验证明:直线边缘定位精度可达0.3pixels,同时为解析曲线亚像素定位提供了一种新的思路。

A new method of sub-pixel localization based on SUSAN and Hough transform was presented. The size of template selection was proposed and the straight edge response was defined in SUSAN algorithm. Meanwhile, weighted Hough transform was conducted. First, the straight edge response was used to extract edge. Then, the Hough transform was computed only when edge points of line had the value of the response and the value was added in an accumulator as a weight. The local areas of parameter space were divided for the second Hough transform and the edge detection was attained by point fitting as sub-pixel localization position. Experimental results show that the sub-pixel localization precision of the method can reach 0.3 pixels. It has greatly decreased calculation compared with traditional edge detection and Hough transform. The method is simple and has better properties of anti-noise capability and robustness. Meanwhile, it provides a new way for sub-pixel localization of analytic curve.