Crop Rows Detection Based on Hough Transform and Fisher Discriminant Criterion Function
基于Hough变换和Fisher准则的垄线识别算法

In this paper green components are used to separate the crop rows from its soil background images.To determine the detection peaks and verify lines in Hough transform,a powerful tool for lines extraction from images in noisy or degraded environment,the conventional Fisher discriminant criterion function is modified to project the sample points in an accumulator into a variable.This is regarded as an efficient measurement for the density and orientation of the points distributing collinearly.An optimal mathematical model for identifying multi-rows is presented.Experimental results show that the algorithm can efficiently eliminate the effect of the weeds,and its accuracy and robustness are improved compared with the conventional Hough transform.And it is useful for the row-recognition system.