一种使用轮廓差分的直线探测算法

A Line Segment Detection Algorithm Using Contour Difference

直线探测是许多有关机器视觉应用场景的一项基本任务。通常,从复杂图像中探测直线需要诸如图像滤波,边缘提取等预处理过程,而这些预处理的质量对直线探测算法具有重大影响。为了规避预处理对后继操作的负面影响,本文引入了一种轮廓差分的概念,来刻画定方向直线存在的可能性,并基于此概念提出一种直线探测的新方法。该方法无需对输入图像进行任何预处理,仅仅在图像平面上直接计算轮廓差分,就可以将直线的探测问题演变成轮廓差分极大值的搜寻问题。对复杂的田间灰度图像的实验表明,本文方法能准确地标记出植株的位置,并且对噪声和模糊等干扰因素也较为鲁棒。

Line segment detection is a fundamental task in the field of machine vision.Usually,the detection processes need various pre-processing,such as image filtering,edge detection and extraction,which have a significant impact on the line segment detection.To tackle this problem,this paper introduced a new concept named contour difference,and presented a new algorithm based on the difference to detect line segments.By use of the new difference,the process of line detection is converted to searching for local maximum in contour differences.The detection algorithm needs no any pre-processing on the input image beyond the calculation of contour difference.Experiments on gray scale field images show that the proposed method can localize most plants accurately,even in the inference of noise and blur.