Detection of small periodic binary signals in image sequences: moving signal sources

摘要

An algorithm developed for detection, localization and tracking of periodic signals, that appear as few-pixel blobs in image sequences and have a characteristic binary pattern in the temporal domain, is described. It is the further development of our original algorithm that extends its capabilities to the detection of moving targets and also improves its performance in some cases. We sketch those stages of the algorithm that were already described and discussed in. Then we describe in full detail the new features of our algorithm, namely: 1) A search for signal sources that move with a relatively-slowly-varying velocity. This velocity is adaptively estimated and re-estimated in order to maximize the correlation with the time-domain pattern. While the first estimate is performed at pixel level, the re-estimation (when tracking detected signals) is performed at the blob level. 2) Re-estimation of the spatial domain background around the already-detected blob, yielding a more precise estimate of the blob. The new algorithm was tested by processing simulated, as well as real, image sequences. The results are discussed. The principal conclusion is that all good features of our original algorithm, namely: efficient detection of visible signals, reasonable detection of invisible signals, insensitivity to local motions in a video, to camera motion, to intensity changes and to any weak flickering of background, remain valid. However, we are required to increase slightly the minimal length of the time-domain correlation (thus, the delay in detection) at the same false alarm probability. Finally, we also consider the problem of the most suitable temporal-domain pattern for signals to be detected.