Indoor Pesticide Smart-Targeting Application Simulation System Based On Machine Vision

Presently the infestation of forest plant diseases and insects in China causes severe problems while the chemical treatment, as the major solution, is of very low efficiency. So, developing "smart" chemical application methods based on the real-time vision sensing technology is urgent and necessary, which bears the promises of low cost and high efficiency of chemical application in diseases and insects treatment and moreover, will protect the forestry ecological environment, shield the operators from the dangerous concoction.In the paper, an indoor-simulation smart chemical application system was developed based on the Theory of Similarity. A series of experiments and analysis, which covered the main puzzles and technical difficulties, were carried out to predict the feasibility and reliability of the system for out-door purposes.Two hardware sub-systems were established in the paper. One was an image capturing sub-system composed of a CCD camera, an image grabber and PC. The other was a smart spray execution sub-system composed of spraying table, nozzles, solenoid-valves and relays. Two sets of software were written in VC++ and assembly language respectively to realize the functions as follows: (1) Real-time capturing, extracting and processing the key frame of tree image from video stream, segmenting the green target from its background by a classifier called relative color indices; (2) Measuring the segmented image by statistic method to obtain morphological and location features of the target, which provides info for intelligent understanding and pattern recognition; (3) Analyzing different camera models, putting forward a tree depth info acquisition algorithm by combining camera model and tree location features; (4) Making an introductory explain for decision making system, putting forward a decision making algorithm by using specific mini-nozzles to control specific zones; (5) Realizing data exchange between PC and SCM, converting decision making results to spraying instructions to control the spray execution system..The research in the paper will provide valuable experiences both theoretically and practically for the outdoor smart chemical applications based on machine vision and the design of plant protection machineries.