Automatic Detection of the Flowers of Endangered Vegetation by Unmanned Aerial Vehicle Observation

Abstract

Although swamps and wetlands are considered valuable ecosystems, it is very difficult to perform field surveillance of such ecosystems because of flooding. Therefore, to develop an automatic classification method for detecting the flowers of the endangered plant species in wetlands, we observed wetland plants using a multirotor-type unmanned aerial vehicle (UAV). We obtained digital images of 76 scenes from approximately 15m above the ground with a spatial resolution of 5mm.
Since the flowers were bright red and the surrounding leaves were green, the flower pixels were extracted based on color and brightness.
To eliminate misclassification, additional filters such as shape, size and surroundings were applied, and the flower pixels were successfully extracted from the images of the target areas. Owing to the accuracy of the classification method, the flowers were extracted at 90.6% recall compared with visual inspection. Thus, the effectiveness of the approach was confirmed.