@article{Srinivasa Rao Gorantla_2020, title={Image Processing System Integrated Multicopter for Diseased Area and Disease Recognition in Agricultural Farms}, volume={13}, url={http://sersc.org/journals/index.php/IJCA/article/view/5135}, abstractNote={<p>Cultivation, these days is more difficult and increasing the labour cost and over usage of pesticides. Enough labour is not available, so labour charges are also increasing which reflects in expenditure for cultivation. For a large field area inspection, each part of the field disease detection is not possible manually and it takes more time and manpower. In this aspect, Multicopters have found their credit in the agriculture industry as they are capable of steady and stable operations. Multicopters can carry multiple sensors and transmit or receive data controls precisely. For identification of diseases in agricultural farms, copters are equipped with a high-quality RGB sensor to move in a predefined path in the field and capture images with Global Position System (GPS) tag at a constant altitude from the ground station. Ground station consists of the high-performance processing system with disease detection algorithm to identify the diseases and provide disease data with a location in the field that will be useful to the farmers where to spray the pesticide in the farm area. In this research work, Multicopter with an RGB sensor is designed to fly in a pre-defined path with the help of Mission Planner and to capture high-quality images. Captured images are undergone image processing analysis using MATLAB software at the ground station. Later healthy and unhealthy plant areas’ GPS information is segregated. Unhealthy plant GPS information is now used to find the actual location of diseased plant area in the overall field.</p&gt;}, number={1}, journal={International Journal of Control and Automation}, author={Srinivasa Rao Gorantla, Venkata Subba Rao Pittu,}, year={2020}, month={Feb.}, pages={219 - 230} }