Vein pattern extraction based on vectorgrams of maximal intra-neighbor difference
Vein pattern extraction based on vectorgrams of maximal intra-neighbor difference
复制标题
基于最大邻内差异向量图的静脉模式提取
DOI：
10.1016/j.patrec.2012.02.020
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发表时间：
2012-10-15
影响因子：
5.1
通讯作者：
Kang, Wenxiong
中科院分区：
文献类型：
--
作者：
Kang, Wenxiong
本文提出了一种用于生物识别的静脉模式提取方法。首先，我们利用原始图像中所有像素的最大内邻差（MIND）向量来表示每个像素与其邻域之间的关系。基于MIND矢量图（MINDVG），我们定义了一个最大的内部邻居矢量差（MIVND）作为一个指标来揭示初步的静脉模式。最后，我们使用一个自适应的阈值来提取纹理模式。该方法的优点在于，结合静脉图像的特点和MINDVG的空间特性，在不进行预处理的情况下，有效地克服了静脉图像厚度不均匀和边界模糊的不利因素。对多幅图像的实验表明，该方法能直接提取出完整清晰的静脉图案，且噪声极小。因此，该算法在静脉模式提取中得到了验证。(C)2012 Elsevier B.V.保留所有权利。
In this paper, a vein pattern extraction method is proposed for biometric purposes. First, we utilize a maximal intra-neighbor difference (MIND) vector of all pixels in the original image to represent the relationship between each pixel and its neighborhood. Based on the MIND vectorgram (MINDVG), we define a maximal intra-neighbor vector difference (MIVND) as an index to unveil the preliminary vein pattern. Finally, we use an adaptive threshold to extract the venation pattern. The advantage of this method is that, by combining the features of vein imaging and the spatial properties of the MINDVG, the algorithm can efficiently overcome the negative factors of inhomogeneous thickness and blurry boundaries in vein imaging without preprocessing. Experiments on several images show that this method can directly extract intact and clear vein patterns with minimal noise. Therefore, the proposed algorithm has been validated in vein pattern extraction. (C) 2012 Elsevier B.V. All rights reserved.