Airport detection by combining geometric and texture features on RASAT satellite images

In this study, a simple and efficient airport detection method is presented. The method is performed uses both the geometric and texture features. The method that use RASAT satellite images is carried out in two stages as coarse and fine stage. In the first stage, line segments are detected with line segment detector (LSD) and the short length of lines are filtered. Remaining line segments are grouped using breadth first search (BFS) to extract airport candidate locations. In the second stage, texture features are calculated using texture around line segments and parallel density feature that is extracted from line segment groups are merged. Finally merged features are classified with support vector machine (SVM) to make detection airport.