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首页> 外文期刊>Journal of visual communication & image representation >Recognition of traffic signs based on their colour and shape features extracted using human vision models
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Recognition of traffic signs based on their colour and shape features extracted using human vision models

机译：根据使用人类视觉模型提取的颜色和形状特征识别交通标志

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摘要

Colour and shape are basic characteristics of traffic signs which are used both by the driver and to develop artificial traffic sign recognition systems. However, these sign features have not been represented robustly in the earlier developed recognition systems, especially in disturbed viewing conditions. In this study, this information is represented by using a human vision colour appearance model and by further developing existing behaviour model of visions. Colour appearance model CIECAM97 has been applied to extract colour information and to segment and classify traffic signs. Whilst shape features are extracted by the development of FOSTS model, the extension of behaviour model of visions. Recognition rate is very high for signs under artificial transformations that imitate possible real world sign distortion (up to 50% for noise level, 50 m for distances to signs, and 5° for perspective disturbances) for still images. For British traffic signs (n = 98) obtained under various viewing conditions, the recognition rate is up to 95%.
机译：颜色和形状是交通标志的基本特征，驾驶员可以使用它来开发人工交通标志识别系统。但是，这些标志特征在较早开发的识别系统中并未得到有力的体现，尤其是在观看条件不佳的情况下。在这项研究中，此信息通过使用人类视觉颜色外观模型以及进一步开发现有的视觉行为模型来表示。颜色外观模型CIECAM97已用于提取颜色信息以及对交通标志进行细分和分类。虽然形状特征是通过FOSTS模型的发展而提取的，但视觉行为模型却得到了扩展。对于模仿静态图像可能出现的现实世界中的符号失真（对于噪声水平高达50％，与符号之间的距离为50 m，对于透视干扰为5°）的人工转换，其符号识别率非常高。对于在各种观看条件下获得的英国交通标志（n = 98），识别率高达95％。

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