Color improves edge classification in human vision
Color improves edge classification in human vision
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DOI：
10.1371/journal.pcbi.1007398
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发表时间：
2019-10-01
影响因子：
4.3
通讯作者：
Kingdom, Frederick A. A.
中科院分区：
文献类型：
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作者：
Breuil, Camille;Jennings, Ben J.;Kingdom, Frederick A. A.
我们的视觉环境包含亮度和颜色（颜色）信息。了解每一个在我们对自然场景的视觉感知中所起的作用是一个持续的研究课题。在这项研究中，我们探讨了颜色线索在一个特定的任务中发挥的作用：边缘分类。我们进行了一项心理物理实验，要求受试者根据图像是否包含颜色信息，将边缘分类为>或>。我们发现，与灰度图像相比，彩色图像的边缘分类性能更好。我们还定义了对简单图像属性敏感的机器观察者，并发现它们也能更好地利用颜色信息对边缘进行分类。结果表明，在自然场景图像中，颜色可以作为边缘分类的线索。尽管视觉世界很复杂，但人类很少将光照（例如阴影）的变化与材料属性（例如油漆或污渍）的变化混为一谈。这种区分照明和材料边缘的能力对于确定自然场景中物体和表面的空间布局至关重要。在本研究中，我们探讨了颜色线索在边缘分类中的作用。我们进行了一项心理物理实验，要求受试者将边缘分为光照和材质，这些边缘取自自然场景的图像，包含或不包含颜色信息。在提取边缘的整个图像的背景下，基于对边缘的检查，将不同尺寸的边缘图像预先分类为照明和材料。与灰度图像相比，发现颜色的边缘分类性能优于灰度图像，与颜色作为边缘分类的线索保持一致。我们定义了对简单图像属性敏感的机器观察者，并发现它们也能更好地利用颜色信息对边缘进行分类，尽管它们未能捕捉到在心理物理实验中观察到的图像大小的影响。我们的发现与之前的研究一致，表明颜色信息有助于识别材料属性、透明度、阴影和阴影形状的感知。
Author summary Our visual environment contains both luminance and color (chromatic) information. Understanding the role that each plays in our visual perception of natural scenes is a continuing topic of investigation. In this study, we explore the role that color cues play in a specific task: edge classification. We conducted a psychophysical experiment that required subjects to classify edges as > or >, depending on whether or not the images contained color information. We found edge classification performance to be superior for the color compared to grayscale images. We also defined machine observers sensitive to simple image properties and found that they too classified the edges better with color information. Our results show that color acts as a cue for edge classification in images of natural scenes.Despite the complexity of the visual world, humans rarely confuse variations in illumination, for example shadows, from variations in material properties, such as paint or stain. This ability to distinguish illumination from material edges is crucial for determining the spatial layout of objects and surfaces in natural scenes. In this study, we explore the role that color (chromatic) cues play in edge classification. We conducted a psychophysical experiment that required subjects to classify edges into illumination and material, in patches taken from images of natural scenes that either contained or did not contain color information. The edge images were of various sizes and were pre-classified into illumination and material, based on inspection of the edge in the context of the whole image from which the edge was extracted. Edge classification performance was found to be superior for the color compared to grayscale images, in keeping with color acting as a cue for edge classification. We defined machine observers sensitive to simple image properties and found that they too classified the edges better with color information, although they failed to capture the effect of image size observed in the psychophysical experiment. Our findings are consistent with previous work suggesting that color information facilitates the identification of material properties, transparency, shadows and the perception of shape-from-shading.