Candidate regions extraction of intruder airplane under complex background for vision‐based sense and avoid system

Abstract

Candidate regions extraction is a crucial problem in object detection. In this study, a new algorithm is proposed for extracting candidate regions of intruder airplane to assist with vision-based sense and avoid system. A key consideration is that the algorithm works well under complex background. The algorithm contains three parts: roughly determining the area of the intruder airplane on the image, segmenting the detected area into image patches and finally extracting candidate regions from the segmented patches. The cycle-frequency filter is adopted to roughly determine the area of the intruder on the image. The graph-based image segmentation method is used to further separate the determined area into the image patches of the intruder and the image patches of the background. The sliding window technique is employed to obtain the regions of interest (ROIs), and the candidate regions of the intruder airplane are finally extracted by merging the overlapped ROIs. The performance of the algorithm is analysed using a number of aerial video sequences with complex background and different angles of view. The results of the experiments indicate the superiority of the proposed algorithm.