Downsampling in uniformly-spaced windows for coding-based Palmprint recognition
Downsampling in uniformly-spaced windows for coding-based Palmprint recognition
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DOI：
10.1007/s11042-023-14574-z
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发表时间：
2023-02
影响因子：
3.6
通讯作者：
Ziyuan Yang;L. Leng;Weidong Min
中科院分区：
文献类型：
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作者：
Ziyuan Yang;L. Leng;Weidong Min
掌纹被认为是最重要的生物识别方式之一。许多基于编码的掌纹识别方法都取得了令人满意的识别效果，这些方法无需训练，存储开销和计算复杂度都很低。下采样通常用于提高实时性，降低存储成本和提高辨别能力。不幸的是，下采样没有得到充分的考虑和研究。在本文中，我们提出了均匀间隔窗口下采样（DUSW），并进行了两个国家的最先进的下采样方法作为其改进版本，被称为均匀间隔极端下采样方法（U-EDM）和均匀间隔民主投票下采样方法（U-DVDM）。在DUSW中，选择每个块中的左上四个像素而不是所有像素来共同决定其值用作该块的代表特征的赢家。DUSW克服了单个像素的独裁，同时确保了相邻获胜者之间足够的空间距离。因此，DUSW降低了相邻获胜者之间的相关性，从而提高了区分度和鲁棒性。同时，计算复杂度仅为原始下采样方法的1/4。充分的实验表明，DUSW可以很容易地嵌入到现有的基于编码的掌纹识别的下采样方法，并提高其识别性能。
Palmprint is deemed as one of the most important biometric modalities. Many coding-based palmprint recognition methods have achieved satisfactory recognition performance, which can be free from training and require low storage cost and computational complexity. Downsampling is typically used to improve real-time ability, reduce the storage cost and improve the discriminative ability. Unfortunately, downsampling was not fully considered and studied. In this paper, we propose downsampling in uniformly-spaced windows (DUSW) and conduct it on two state-of-the-art downsampling methods as their reformative versions, dubbed uniformly-spaced extreme downsampling method (U-EDM) and uniformly-spaced democratic voting downsampling method (U-DVDM). In DUSW, the upper-left four pixels rather than all pixels in each block are selected to jointly decide the winner whose value is used as the representative feature of this block. DUSW overcomes the dictatorship of a single pixel and simultaneously ensures the sufficient spatial distance between the adjacent winners. Thus, DUSW reduces the correlation between the adjacent winners, and accordingly improves the discrimination and robustness. Meanwhile, the computational complexity is only 1/4 of the original downsampling methods for the representative reduction. The sufficient experiments demonstrate that DUSW can be easily embedded into the existing downsampling methods of coding-based palmprint recognition and improve their recognition performances.