APPLICATION OF GROUND PICTURE TO RIVER PATROL BY THE IMAGE RECOGNITION AI AND UAV — VERIFICATION OF THE FEATURES VALUE, AND THE USAGE—

Abstract

Japan has many rivers, and the almost management work is carried out manually. Due to the development of drone (UAV) technology, they are applied to river monitoring, and the research with AI, such as using the image taken by drone for detect illegal dumping, is also increasing. On the “ground”, taking a lot of picture for report by humans requires hard work and is also subject to the diversity of condition. The aerial image has a different angle of view from the ground image and the conditions are different. In this research, whether can utilize the ground image of river maintenance management database system RiMaDIS to improve the detection accuracy in less aerial image are verified. The image of illegal dumping taken from ground and drone are classified by three image feature value, and they were learned by Faster R-CNN. The verification result suggests that features value such as Bounding Box occupancy contribute to the improvement of detection accuracy.