This paper presents a system designed to estimate object positions and detect the presence of objects using image data captured by a monocular camera mounted on a drone. The testing of the method was conducted using a controller algorithm, where a drone was flown laterally in front of two miniature plants, capturing images for object detection and position estimation via triangulation. The system was able to reduce triangulation errors after multiple detections of the same object, achieving improved accuracy. Further real-world testing demonstrated the system's ability to avoid obstacles and successfully navigate toward predefined target positions. The results indicate that the presented image processing algorithm can serve as a reliable input for target search and pathfinding applications, with potential future applications in monitoring tasks, such as transmission line inspections.