Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which
would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex
circumstance, quick and precise detection of FOD target on the runway is one of the important protections for
airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is
introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD
is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by
millimeter-wave radar, and then according to the coordinate IR camera will take target images and
background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by
using Hough transformation method. The potential target region, that is, runway region, can be segmented
from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region.
Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target
classification. The experiment results show that this algorithm can effectively reduce the computational
complexity, satisfy the real-time requirement and possess of high detection and recognition probability.