Flying Objects Extraction Based On A Steadiness Analysis From Image Sequences

Abstract

A new approach for the extraction of flying objects in the presence of a perturbed background is presented. The approach is based on a steadiness analysis of moving objects from image sequences and has been implemented on the Pipelined Image Processing Engine (PIPE). Trees are "steadier" than flying airplanes as a tree's top moves in a confined area. However, an airplane typically moves in a fixed direction for an extended period of time. This simple constraint is exploited as the basis for utilizing an object's "steadiness" in the extraction of flying objects. The algorithm proceeds in three passes. First, an image-differencing operation is used to extract flying objects and swinging objects (e.g., tree); secondly, a mask covering a swinging object's moving area is created by studying the steadiness of flying objects and swinging objects over a couple of frames; thirdly, the mask created in the second pass is used to guide the extraction of flying objects from subsequent frames. The performance of this approach has been tested on a number of sequences of synthetic and real-world images. It has been found that the algorithm is accurate and robust for extracting flying objects. A number of limitations of the algorithm have been proposed and their effects on performance have been studied.