Research On The Spray Control System Aiming At Weed Based On Machine Vision

The usage method of chemistry herbicide is wide-spread to spray, spraying isn't to aim at a target thing accurately, but usually spraying at the soil without weed, so plenty of herbicide is wasted , resulting in not only the Human body hurt easily, but also the ecosystem environment crisis and increasing agricultural chemicals residue. Along with a great deal of usage of pesticide and herbicide, the hurt to the human body and the environment increase with each passing day. It is opposite to the modern agriculture which require precision, efficiency and Environment friendliness. For reducing cost and protecting environmental, the research of spraying precisely is done by more and more people, hoping it can take the place of the traditional spraying method, so the labor condition and the efficiency of herbicide can be improved and the pollution of environment can be avoided.The distributing of weed in the field is random and asymmetry. The discontinuity of weed distributing provide a basis for the precise-spraying. Because the constant row spacing is good for weed identification, the spraying control system aiming at weed in row wheat based on machine vision was designed and developed on the basis of research on abroad and domestic. The contents of the study could be briefly summarized as follows:1.Image segmentation based on color characteristic is researched. The segmented result and consuming time about 13 factors of color were researched contrastively. The research result was the exceed green 2G-R-B is the best segmented factor.2.Image segmentation based on taking threshold automatically can process the image in time. The algorithm of combining maximum variance and minimum error is designed. The contrast research certificate the algorithm is better to the other two algorithm.3.Aiming at the alike characteristic of weed structure, the weed and weed leaf fractal characteristic was researched and algorithm of calculating fractal dimension is designed. The analysis of weed fractal dimension verified it can be used for weed identification effectively.4.The calculating method of statistical texture value based on gray co-occurrence and the texture value of weed and wheat under different sunshine were analysised. The texture value is not sensitive to the sunshine and it can be used for weed identification. 5.Aiming at the position characteristic of constant spacing, the method of obtaining the center line of crop rows is researched. The improved pixel lateral histogram algorithm for extracting the center of crop row is designed. The infield adaptability of the algorithm was enhanced by subsection computation. Other three method of extracting the center of crop row is also studied.6. Aiming at advantage of pattern recognition of ANN, three layer BP ANN is designed for the experiment of weed identification. The experimental result is that the ANN cold be used for weed identification based on texture value or/and fractal dimension.7.The spraying control system aiming at weed based on machine vision was designed and developed. The index of 2G-R-B is used for segmentation and the method of improved pixel lateral histogram is used for extracting the center of crop row,the method of threthold is also used for identificating between-row weed and BP ANN based on fratal and texture is used for identificating in-row weed. PLC correspondence and performing procedure is desi -gned and developed. Spraying performing system is designed and assembled.8. The experiment was done on a plot modifying wheat field, the result verified that the control system is able to spray selectively.