UAV Traffic Patrolling via Road Detection and Tracking in Anonymous Aerial Video Frames

Autor: Mucahit Karaduman, Ahmet Çinar, Haluk Eren
Rok vydání: 2019
Předmět:
Zdroj: Journal of Intelligent & Robotic Systems. 95:675-690
ISSN: 1573-0409
0921-0296
DOI: 10.1007/s10846-018-0954-x
Popis: Unmanned Aerial Vehicles (UAV) have gained great importance for patrolling, exploration, and surveillance. In this study, we have estimated a route UAV to follow, using aerial road images. In the experimental setup, for estimation, test, and validation stages, anonymous aerial road videos have been exploited, meaning a special image database was not produced for this simulation approach. In the proposed study, road portion is initially detected. Two methods are utilized to help road detection, which are k-Nearest Neighbor and Hough transformation. To form a decision loop, both results are matched. If they match each other, they are fused using spatial and spectral schemes for the comparison purpose. Once road area is detected, the road type classification is realized by Fuzzy approach. The resultant image is utilized to estimate route, over which the UAV have to fly towards that direction. In the simulation stage, an anonymous video stream previously captured by UAV is experimented to assess the performance of the underlying system for different roads. According to the implementation results, the proposed algorithm has succeeded in finding all the trial roads in the given aerial images, and the proportion of all the estimated road-portion to actual road pixels for all the images is averagely calculated as %95.40. Eventually, it is shown that UAV has followed the correct route, which is estimated by proposed approach, over the specified road using assigned video frames, and also performances of spatial and spectral fusion results are compared.
Databáze: OpenAIRE
Externí odkaz: