The Edge detection is a customarily task. Edge detection is the main task to perform as it gives clear information about the images. It is a tremendous device in photograph processing gadgets and computer imaginative and prescient. Previous research has been done on moving window approach and genetic algorithms. In this research paper new technique, Bacterial Foraging Optimization (BFO) is applied which is galvanized through the social foraging conduct of Escherichia coli (E.coli). The Bacterial Foraging Optimization (BFO) has been practice by analysts for clarifying real world optimization problems arising in different areas of engineering and application domains, due to its efficiency. The Brightness preserving bi-histogram equalization (BHEE) is another technique that is used for edge enhancement. The BFO is applied on the low level characteristics on the images to find the pixels of natural images and the values of F-measures, recall(r) and precision (p) are calculated and compared with the previous technique. The enhancement technique i.e. BBHE is carried out to improve the information about the pictures.

Automating the tasks that require manpower has been considered as an area of active research in science and technology. Challenges in designing such systems include accuracy in the parameters of performance, minimal hardware, cost-efficiency, and security. The efficiency of drones designed for replacing humans is often evaluated using their weight, flying time, and power consumption. Herein, the prototypebased Drone model has been designed and discussed for horticulture applications. In this model, a horticulture drone has been designed for structuring and cutting of plants in street interstates. This methodology focuses on automation engineering that is utilized for cutting the plants in less time and less power, thereby diminishing the contamination that may happen by utilizing fuels. The epic part of this plan includes the less weight drone predesigned using Computer-Aided Three-Dimensional Interactive Application (CATIA) V5 Software. The throttle for the motors is adjusted at 50% to get the required thrust for the Unmanned Aerial Vehicle (UAV) to fly. Experimental results show that the horticulture drone has comparatively more flying time and less power consumption.