Fusion of color spaces for ear authentication
Fusion of color spaces for ear authentication
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DOI：
10.1016/j.patcog.2008.10.016
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发表时间：
2009-09
期刊：
影响因子：
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通讯作者：
L. Nanni;A. Lumini
中科院分区：
文献类型：
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作者：
L. Nanni;A. Lumini
在这项工作中，我们提出了一种基于不同颜色空间训练的匹配器集合的2D耳朵认证的本地方法。这是第一个工作，提出利用强大的属性的颜色分析，以提高性能的耳匹配。所描述的方法是基于颜色空间的选择，从该颜色空间中提取一组Gabor特征。选择使用顺序前向浮动选择来执行，其中适应度函数与人耳识别性能的优化相关。最后，匹配步骤是通过组合的总和规则的几个1-近邻分类器构建在不同的颜色分量。使用Notre-Dame的数据集证明了所提出的方法的有效性。特别有趣的是，新方法在rank-1（1084%），rank-5（1093%）和ROC曲线下面积（1098.5%）方面获得的结果，优于其他最先进的2D耳匹配器。
In this work, we propose a local approach for 2D ear authentication based on an ensemble of matchers trained on different color spaces. This is the first work that proposes to exploit the powerful properties of color analysis for improving the performance of an ear matcher. The method described is based on the selection of color spaces from which a set of Gabor features are extracted. The selection is performed using the sequential forward floating selection where the fitness function is related to the optimization of the ear recognition performance. Finally, the matching step is performed by means of the combination by the sum rule of several 1-nearest neighbor classifiers constructed on different color components. The effectiveness of the proposed method is demonstrated using the Notre-Dame EAR data set. Particularly interesting are the results obtained by the new approach in terms of rank-1 (∼84%), rank-5 (∼93%) and area under the ROC curve (∼98.5%), which are better than those obtained by other state-of-the-art 2D ear matchers.