In view of the long and narrow characteristics of the airport runway function area, this paper proposes a method combining the Haar -like feature and the spherical neural network to detect the airport runway in remote sensing images. The algorithm first uses Haar-like to extract the target features and trains the strong classifier, and then further uses a spherical neural network model to eliminate false alarms. The experimental results show that the algorithm achieves good accuracy in detecting airport runways.
Research on a Method of Airport Runway Detection Algorithm
01.07.2019
3648639 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
SAE Technical Papers | 2016
Algorithm Research for Function Damage Assessment of Airport Runway
Springer Verlag | 2016
|Transportation Research Record | 2013
|