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首页> 外文会议>Sixth International Conference on Quality Control by Artificial Vision May 19-22, 2003 Gatlinburg, Tennessee, USA >Estimation of the luminance map for Lambertian photometric model: Application to the study of a road surface roughness
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Estimation of the luminance map for Lambertian photometric model: Application to the study of a road surface roughness

机译：Lambertian光度模型的亮度图估计：在路面粗糙度研究中的应用

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摘要

The study of rough textured surface as road coverings, are generally made on grey level images. This suppose, that the variations of grey levels are representative of the local variations of the relief. This justified assumption, in the case of surfaces uniformly colored, finds its limit in the case when these surfaces present variations of color or aspect. The corresponding image will then present variations of grey levels which can be related to the color variations or to the relief variations or both. It then becomes difficult in this case to work out criteria of roughness based on image analysis. It is then necessary to work out, before any study of roughness, an estimation of the luminance map linked to color variations. In order to do that, we have linked the grey level value to the height variation of the road covering surface. So we have expressed the luminance distribution according to these height variations, obtained through a laser sensor, and to the image grey level. The suggested method allows us to compute the distribution of the luminance map. We characterise this distribution by considering statistical parameters of its histogram. We have tested the effectiveness of our approach by comparing the evolutions of the criteria of roughness on road surfaces, without considering the luminance distribution and by taking it into account. The results obtained show that the developed approach leads to a good discrimination by the criteria of roughness in the case of colored surfaces.
机译：通常在灰度图像上研究粗糙的纹理表面作为道路覆盖物。假设灰度的变化代表浮雕的局部变化。在表面均匀着色的情况下，这种合理的假设在这些表面呈现颜色或外观变化的情况下找到了极限。然后，相应的图像将呈现灰度级的变化，该灰度级的变化可能与颜色变化或浮雕变化或两者有关。因此，在这种情况下，难以基于图像分析来确定粗糙度的标准。因此，在进行粗糙度研究之前，有必要对与颜色变化有关的亮度图进行估算。为此，我们将灰度值与道路覆盖表面的高度变化相关联。因此，我们已经根据通过激光传感器获得的这些高度变化以及图像灰度表示了亮度分布。建议的方法使我们可以计算亮度图的分布。我们通过考虑直方图的统计参数来表征这种分布。我们通过比较道路表面粗糙度标准的演变（不考虑亮度分布）并将其考虑在内，测试了我们方法的有效性。获得的结果表明，在有色表面的情况下，所开发的方法可以根据粗糙度标准很好地进行区分。

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