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融合颜色属性和空间信息的显著性物体检测

DOI: 10.11834/jig.20140407

Keywords: 颜色属性,视觉显著性,区域对比度,空间紧致性,路标检测

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Abstract:

目的提出了一种基于颜色属性和空间信息的显著性物体检测算法,并将其用于交通标志的检测。方法首先,训练颜色属性得到颜色-像素值分布,据此将图像划分为不同的颜色聚簇,每个聚簇的显著性取决于其空间紧致性。其次,将每个聚簇分割为多个区域,用颜色属性描述子表示每个区域,计算区域的全局对比度。最后,同时考虑区域对比度和相应聚簇的空间紧致性,得到最终的显著图。在此基础上,将交通标志的先验知识转换为自上而下的显著性图,形成任务驱动的显著性模型,对交通标志进行检测。结果在公开数据集上的测试结果表明,该算法取得最高92%的查准率,优于其他流行的显著性算法。在交通标志数据集上的检测取得了90.7%的正确率。结论提出了一种新的显著性检测算法,同时考虑了区域的颜色和空间信息,在公开数据集上取得了较高的查准率和查全率,在对交通标志的检测中也取得了较好的结果。

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