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Extraction of Moving Objects on Underwater Video Using Method of Subtraction the Background Modeling Results

机译：减去背景建模结果的方法提取水下视频中的运动对象

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This paper proposes a method for extracting moving objects on an underwater surveillance video. Video obtained using an underwater camera to capture the environmental conditions of the area. This research is the initial stage of the underwater surveillance system. Underwater surveillance system enables objects passing can be recognized shapes, types, and its behavior. The extraction method used in this research is a subtraction between the current frames with the background modeling results. Underwater video retrieval has a high level of difficulty because the background is always changing either due to a change the intensity and the movement of water currents. Therefore, it needs to be made an appropriate background model to address this problem. Modeling of the background on this research using adaptive modeling method, where the intensity of the background pixels is updated based on inference of the background intensity before. If the intensity of the pixels changed drastically beyond the allowed threshold value, the pixel is considered as the pixels of the object and the pixel values of the background model are updated based on this pixel value. The effectiveness of the proposed method is expressed with the value of recall and precision. The average recall value of the three videos is 62% and the value of its precision is 82%. Keyword s --- Extraction Object, Background Modeling, Adaptive Modeling, underwater surveillance.
机译：本文提出了一种在水下监控视频中提取运动物体的方法。使用水下相机获取的视频以捕获该区域的环境条件。这项研究是水下监视系统的初始阶段。水下监视系统使通过的物体可以被识别的形状，类型及其行为。本研究中使用的提取方法是将当前帧与背景建模结果相减。水下视频检索具有很高的难度，因为由于水流的强度和运动的变化，背景总是在变化。因此，需要将其设为合适的背景模型来解决此问题。在本研究中，背景采用自适应建模方法进行建模，其中背景像素的强度根据之前的背景强度推断进行更新。如果像素的强度急剧变化超过允许的阈值，则将该像素视为对象的像素，并基于该像素值更新背景模型的像素值。所提方法的有效性体现在召回率和精确度上。这三个视频的平均召回价值为62％，其精确度值为82％。关键字s ---提取对象，背景建模，自适应建模，水下监视。

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