Abstract:
Agriculture is the most important source of livelihood. Crop segmentation has become an important role in precision agriculture which helps farmers to make decisions about crop damage and its production. However, it's a challenging task to achieve precision in the agriculture field. Drone Surveillance helps to achieve that crop yield assessment, crop damage, crop health, and other parameters. This paper focuses on image segmentation of crops, classified into categories like sparse and dense crops with the multitemporal data image taken by Drone. This model proposed and studied shows the loss percentage in crop identification by image segmentation process, it helps farmers to get good compensation for crops to survey through Drone (UAV) techniques. A detailed analysis with outcome of thisis explained further.