A Novel Airport Detection Method via Line Segment Classification and Texture Classification


Airports are one among the most necessary traffic facilities; thus, airport detection is of great significance in economic and military construction. This letter proposes a unique method for airport detection, with the whole algorithm based on line section classification and texture classification. Initial, a quick line phase detector is applied to extract the line segments in images and compute the options of these line segments. Then, the line segments are discriminated by a trained runway line classifier, and therefore the regions of interest (ROIs) are extracted from the line segments, that are classified as runway lines. Finally, whether or not the ROI is actually an airport is decided by analyzing the classification results of the image blocks. This technique is unique in terms of the computing of line phase options and line section classification. Experimental results demonstrate the effectiveness and robustness of the proposed method.

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