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Outdoor Scene Image Segmentation Based on Background Recognition and Perceptual Organization

机译:基于背景识别和感知组织的户外场景图像分割

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In this paper, we propose a novel outdoor scene image segmentation algorithm based on background recognition and perceptual organization. We recognize the background objects such as the sky, the ground, and vegetation based on the color and texture information. For the structurally challenging objects, which usually consist of multiple constituent parts, we developed a perceptual organization model that can capture the nonaccidental structural relationships among the constituent parts of the structured objects and, hence, group them together accordingly without depending on a priori knowledge of the specific objects. Our experimental results show that our proposed method outperformed two state-of-the-art image segmentation approaches on two challenging outdoor databases (Gould data set and Berkeley segmentation data set) and achieved accurate segmentation quality on various outdoor natural scene environments.
机译:在本文中,我们提出了一种基于背景识别和感知组织的新型户外场景图像分割算法。我们根据颜色和纹理信息识别背景对象,例如天空,地面和植被。对于通常由多个组成部分组成的具有结构挑战性的对象,我们开发了一种感知组织模型,该模型可以捕获结构化对象的组成部分之间的非偶然结构关系,因此,无需依赖于先验知识就可以将它们组合在一起具体对象。我们的实验结果表明,在两个具有挑战性的室外数据库(Gould数据集和Berkeley分割数据集)上,我们提出的方法优于两种最新的图像分割方法,并且在各种室外自然场景环境下均达到了准确的分割质量。

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