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Automatic object detection and segmentation from underwater images via saliency-based region merging

机译:通过基于显着性的区域合并从水下图像中自动进行对象检测和分割

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Underwater object detection and segmentation has been attracting a lot of interest, and recently various systems have been designed. In this paper, we introduce a novel technique to automatically detect and segment objects from underwater images via saliency-based region merging. The method is composed of three main steps. Firstly, a salient object detection model is used to detect the position of salient objects in underwater image. Secondly, background prior is applied to determine the approximate background location. Thirdly, the region merging based interactive image segmentation method is improved by adding the determined object and background location information as the user inputs so that the algorithm becomes automatic. The experimental results show that it's efficient to segment objects from the underwater image by the proposed method.
机译:水下物体检测和分割吸引了很多兴趣,并且最近已经设计了各种系统。在本文中,我们介绍了一种新技术,可以通过基于显着性的区域合并从水下图像中自动检测和分割对象。该方法包括三个主要步骤。首先,使用显着物体检测模型来检测水下图像中显着物体的位置。其次,应用背景先验来确定背景的大概位置。第三,通过在用户输入时添加确定的对象和背景位置信息,改进了基于区域合并的交互式图像分割方法,从而使算法变得自动。实验结果表明,该方法能有效地从水下图像中分割出物体。

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