In t h e case of a marine casualty occurs, the detection of the rescue target such as life rafts depends on the visual search by man as yet. However, human eyes sometimes lose its sight owing to a long flight and wide views. In order to carry out the prompt rescue of human life, development of t h e searching system in place of t h e human eyes is surely required. This paper deals with a new search method for detection of the rescue target using image processing techniques. To detect t h e small target in t h e wide views over t h e sea, we have proposed a new method including t h e image processing techniques based on t h e color information and t h e c o m p o s i t e image sensor which increases about t h emeasurement accuracy and the image processing speed at actual field. A t t h e first step of t h e study, we attempt ta extract the image data o f t h e rescue target with t h e orange color i n an experimental sea.

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Abstract:For underwater port surveillance, it is important to develop a technique that can automatically detect slow-moving targets such as divers. It is difficult to detect such targets since their echoes are masked by undesirable signals such as random noises, reverberations, wake bubbles, echoes of static objects, and crosstalk noises generated by multibeam processing. To detect moving targets effectively, a signal processing method that can eliminate only these undesirable signals is required. However, conventional methods that deal with only signal amplitude cannot remove these undesirable signals easily since random temporal fluctuations of amplitudes are incorrectly identified as moving targets, leading to many false detections. We propose a new signal detection method that uses an interferometric technique that can effectively eliminate only the undesirable signals, and detect moving targets.The proposed method deals with temporal fluctuations of phase difference measured by the split-beam method independently from amplitude-based methods. The spatiotemporal fluctuation of phase difference is closely related to the movement of a target, and it is possible to detect moving targets effectively by evaluating the spatiotemporal variance of the phase difference. In this study, the authors developed an algorithm for the proposed target detection method. By applying the proposed method to experimental data, we have confirmed that it has high detection performance compared to conventional methods.Classification: Signal Processing and Miscellaneous (Observations, Measurements, etc.)