International Journal of Information Technology & Computer Science ( IJITCS )
Precision herbicide applicator systems offer the promise of increasing productivity by optimizing herbicide usage based on weed density. In this paper, a real-time precision herbicide applicator system is developed and mounted with a tractor. The system composes of two main components: weed monitoring and real-time sprayers. The proposed system is a machine vision based approach. Input images of a field are captured using a web camera mounted on a moving tractor. Greenness level of weeds in each image are processed using the Offset Excessive Green (OEG) combined with Non Green Subtraction (NGS) technique. The proposed weed monitoring algorithm can work under natural illumination condition without any assistant light diffuser. The percentage of the obtained greenness is used to actuate the controllers of a spryer system. From our experimental results, the proposed method is robust under illumination variations. Weeds under different lighting conditions are reliably detects. In field tests, the proposed applicator system working at constant moving speed could spray on weed targets correctly. The proposed method is also very effective, especially in sparse weed density condition. The proposed system is fast. suitable for using in real-time application.
: Precision herbicide applicator; variable rate applicator; machine vision; weed density estimation
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