基于机器视觉的麦田边界检测

Edge Detection for Wheat Field Based on Machine Vision

针对不同时期麦田场景,提出了基于机器视觉的边界(田埂)检测算法。将摄像机安装在农田作业机械前方,在作业过程中采集麦田场景图像。根据麦田和田外区域的不同颜色及亮度特征,判断出田埂的位置以及田埂线的方向候补点群,使用过已知点的哈夫变换计算出田埂线的斜率。经过对多幅不同时期麦田图像的处理,证明本检测算法可以适应不同时期的麦田环境,并且具有速度快、抗干扰、准确性高等优点。

According to various wheat field conditions in different phases, the field-edge detection algorithm based on machine vision was put forward. The camera mounted in front of the tractor could capture the images wheat field during the process of working. With the color and luminance difference of wheat field and outside the field, the position of field-edge and the candidate points of it could be detected~ the slope of the field-edge was calculated by using passing a known point Hough transform. Test results showed that the method was suitable for different wheat field phases and has characteristics of fast speed, high veracity and resisting interference.