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Interactive Segmentation of Color Images Based on Color Saliency

机译:基于色彩显着性的彩色图像交互式分割

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Efficient interactive foreground extraction from color images is of great practical importance in computer vision. In recent years, an approach based on optimization using graph-cuts has been widely used. However, an interactive foreground extraction approach, which is intuitive and efficient for users, is required for practical applications. In this paper, we propose a novel interactive foreground extraction method based on color saliency. In our method, the user provides only some foreground pixels as the initial reference. To achieve extraction of multiple target objects, the likelihoods of the foreground and background are defined by a Gaussian mixture model and a color saliency map based on the provided reference pixels. These likelihoods are added to the cost of the proposed graph. Finally, image segmentation is performed by optimizing the proposed graph using the graph-cut algorithm.
机译:从彩色图像中进行有效的交互式前景提取在计算机视觉中非常重要。近年来,基于使用图割的优化的方法已被广泛使用。然而,实际应用需要交互式的前景提取方法,该方法对于用户是直观且有效的。本文提出了一种基于显着性的交互式前景提取方法。在我们的方法中,用户仅提供一些前景像素作为初始参考。为了实现多个目标对象的提取,前景和背景的可能性由高斯混合模型和基于提供的参考像素的颜色显着性图定义。这些可能性被添加到拟议图的成本中。最后,通过使用图割算法优化提出的图来执行图像分割。

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