Research On The Identification Of Weed Images In Fields

The identification technology of weed images in wheat fields was studied in this paper and a software system of weed images identification has been designed.The major content includes collecting images using digital camera; pretreating images; partitioning the green plants and the soil which includes again transforming the color images into grey images, and transforming the images' formats, and transforming the grey images into binary images; partitioning the crop and the weed which includes again the identification of the center line of the crop and filtering of the crop line; finally obtaining the weed images. In order to compute the boundary of crop line, this paper choose different thresholds to compute the relative error between the automatically detected crop line width and the manually defined crop line width, and finally choose the appropriate threshold that minimum error.The template matching and the neural network recognition method are separately used to identify the position of weed.Template matching identification method is: Choosing a grass from the image to take the characteristic data of the template, moving a template picture from one element to another element in the image, Namely searching the region of the original map like the template and seek the match spots, and searching the window and characteristics of the goal object shape to realize the goal's examination and the track as the criterion. computing Euclidean distance between the elements of template picture and the elements of the operating position of template in the original picture. If the Euclidean distance is closer 0, the match degree is higher. searching the highest matched degree spots. Weeds'pictures are composed by them. In the image its demonstrates white, and it express in the image by the white spots, and the pictures are composed by other elements. In the image its demonstrates black. If the weeds' coordinated positions are computed, thus had achieved intention of seeking the weed position goal.The neural network identification method is: It use the BP neural network sorter of 3 tiers to car divide up for the weed image completely. The level unifies the way completely the BP neural network division sickness spot image. Input characteristics are each picture's elements: H, Cb, Cr value, therefore the number of neuron center of input level is 3; the number of neuron center of Output level is 1. Then output signal from 0 to 1. If the output signal is bigger than 0.9, the image is weed. In the image it is demonstrated white; If the output signal is smaller than 0.1, the corresponding input signal picture element is the soil background, in the image it is demonstrated black. Enables the network through the training to achieve stably, finally uses the MATLAB toolbox to divide the image, then the image demonstrates white spots' positions namely for weeds' positions.This system was programmed by MATLAB language. So the system can successfully filter out the crop lines and identify the weeds' positions.