A Novel FOD Classification System Based on Visual Features

In this paper, we propose a novel framework of Foreign Object Debris (FOD) classification system. The system contains a FOD detection subsystem, electro-optical subsystem and the control center. The system not only provides continuous surveillance of scanned surfaces and achieves the goal of FOD detection, but also performs FOD classification. Both low level features and subspace features are compared to extract the FOD. Multiclass classifiers are trained in all the candidate feature spaces with the Support Vector Machine (SVM) to classify FOD. Experimental results show that it is promising to classify FOD with low-level features.