ID 原文 译文
24785 算法首先使用 FCM 聚类产生一组有差异性的基聚类成员，并通过阴影集构造三支聚类。 First, the algorithm generates a set of clustering members using the fuzzyc-means algorithm, and then the membership degree is mapped into three regions to construct three-way clustering.
24786 然后引入多粒度粗糙集构建了四个近似集合，将每一个类簇划分为一个核心域和三个边界域。 Second, the multi-granulation rough sets are used to construct four different approximate regions. Each cluster contains a core region and three boundary regions.
24787 最后对边界域中的数据依次划分到核心域中，无法划分的对象则留在边界域，最终得到了三支聚类集成的结果。 Finally, the shadowed set is used to classify objects in boundary regions sequentially. Objects that cannot be divided are left in the boundary region.
24788 实验结果表明，本算法在准确率、调整兰德系数和归一化互信息方面，与多种现有的聚类集成算法相比得到了更好的聚类集成结果。 The experimental results show the algorithm obtains better clustering ensemble results in accuracy, adjust rand index, and normalized mutual information compared to multiple existing clustering ensemble algorithms.
24789 三维掌纹能显著地减少应用过程中潜在的安全隐患，近年来吸引了越来越多的关注。 Three dimensional (3D) palmprint could efficiently reduce potential security risks in practical applications, and thus attracts a growing interest in recent years.
24790 然而，现有的三维掌纹识别方法大多借助人工设计的描述符来进行匹配，这往往需要先验知识。 However, most existing 3D palmprint recognition methods require hand-craft designed descriptors and strong prior knowledge are needed.
24791 本文提出一种基于学习策略的局部方向特征二进制编码来完成三维掌纹识别。 In this paper, we propose a local direction binary code learning method for 3D palmprint recognition.
24792 该方法利用形状指数来描述三维掌纹的局部几何特征，并且在形状指数图像上计算 Gabor 滤波器响应并将响应差值组合起来形成特征向量。 We employ shape index representation to demonstrate the geometry characteristics of local regions in 3D palmprint data, and form Gabor filter response difference vector as the feature vectors by applying the Gabor filter on the shape index image.
24793 提出利用哈希学习模型得到特征映射函数并将响应差值特征向量转换为方向特征二进制编码，并对方向特征二进制编码图采用分块策略形成特征直方图来进行匹配。 We utilize the hash learning model to learn feature mapping functions that can project these feature vectors into direction binary code, and further construct the block-wise histograms for matching.
24794 在香港理工三维掌纹数据库上的实验结果表明，本文方法在识别率上要优于目前流行的其他三维掌纹识别方法，从而验证了本文方法的有效性。 Experiments on Hong Kong Polytechnic University 3D palmprint database validate that our method outperforms existing state-of-the-art methods in terms of recognition accuracy, showing the effectiveness of our method.