Evaluating color texture descriptors under large variations of controlled lighting conditions
Evaluating color texture descriptors under large variations of controlled lighting conditions
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DOI：
10.1364/josaa.33.000017
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发表时间：
2016-01-01
影响因子：
1.9
通讯作者：
Schettini, Raimondo
中科院分区：
文献类型：
--
作者：
Cusano, Claudio;Napoletano, Paolo;Schettini, Raimondo
在不同光照条件下对颜色纹理的识别仍然是一个有待解决的问题。为此已经提出了几个特征，从传统的统计描述符到用神经网络提取的特征。尽管如此，在什么情况下一个特性比其他特性表现得更好还不完全清楚。在本文中，我们报告了新旧纹理特征的广泛比较，有和没有颜色归一化步骤，特别关注这些特征如何受到照明条件下大小变化的影响。评估是在一个新的纹理数据库上进行的，该数据库包括在46种条件下获得的68个生食样品，这些条件呈现光的颜色、方向和强度的单一和组合变化。该数据库使我们能够系统地研究纹理描述符在成像条件大变化中的鲁棒性。(C) 2015美国光学学会
The recognition of color texture under varying lighting conditions remains an open issue. Several features have been proposed for this purpose, ranging from traditional statistical descriptors to features extracted with neural networks. Still, it is not completely clear under what circumstances a feature performs better than others. In this paper, we report an extensive comparison of old and new texture features, with and without a color normalization step, with a particular focus on how these features are affected by small and large variations in the lighting conditions. The evaluation is performed on a new texture database, which includes 68 samples of raw food acquired under 46 conditions that present single and combined variations of light color, direction, and intensity. The database allows us to systematically investigate the robustness of texture descriptors across large variations of imaging conditions. (C) 2015 Optical Society of America