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首页> 外文期刊>Pattern Analysis and Machine Intelligence, IEEE Transactions on >Describing Reflectances for Color Segmentation Robust to Shadows, Highlights, and Textures
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Describing Reflectances for Color Segmentation Robust to Shadows, Highlights, and Textures

机译：描述针对阴影，高光和纹理的色彩分割的反射率

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摘要

The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost.
机译：由于由物体的几何形状，阴影和镜面反射引起的图像测量值的巨大变化，单一材料反射率的分割是一个具有挑战性的问题。这些效果的组合已通过双色反射模型建模。但是，由于未知的采集参数和压缩伪像，模型在实际图像中的应用受到限制。在本文中，我们为直方图空间中单个材料反射率的形状提供了一个健壮的模型。该方法基于直方图的多局部折痕分析，该分析会导致代表材料反射率的一组脊线。从这些山脊得出的分割方法对于真实世界图像中的阴影，阴影和镜面反射以及纹理都具有鲁棒性。我们通过结合图像统计中的先验知识来进一步完善该方法，并通过使用多尺度色彩对比信息来结合空间一致性。获得的结果表明，在广泛使用的分割基准上，我们的方法明显优于最新的分割方法，其主要特征是在阴影和高光的情况下以较低的计算成本提供了出色的性能。

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