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Principal line-based alignment refinement for palmprint recognition

机译:基于主线的对齐细化用于掌纹识别

摘要

Image alignment is an important step in various biometric authentication applications such as palmprint recognition. Most of the existing palmprint alignment methods make use of some key points between fingers or in palm boundary to establish the local coordinate system for region of interest (ROI) extraction. The ROI is consequently used for feature extraction and matching. Such alignment methods usually yield a coarse alignment of the palmprint images, while many missed and false matches are actually caused by inaccurate image alignments. To improve the palmprint verification accuracy, in this paper, we present an efficient palmprint alignment refinement method. After extracting the principal lines from the palmprint image, we apply the iterative closest point method to them to estimate the translation and rotation parameters between two images. The estimated parameters are then used to refine the alignment of palmprint feature maps for a more accurate palmprint matching. The experimental results show that the proposed method greatly improves the palmprint recognition accuracy and it works in real time.
机译:图像对齐是各种生物认证应用(例如掌纹识别)中的重要步骤。大多数现有的掌纹对齐方法都利用手指之间或手掌边界中的一些关键点来建立感兴趣区域(ROI)提取的局部坐标系。因此,ROI用于特征提取和匹配。这种对准方法通常会产生掌纹图像的粗略对准,而实际上许多不匹配和错误匹配都是由不正确的图像对准引起的。为了提高掌纹验证的准确性,本文提出了一种有效的掌纹对齐细化方法。从掌纹图像中提取主线后,我们对其应用迭代最近点法,以估计两幅图像之间的平移和旋转参数。然后,将估计的参数用于完善掌纹特征图的对齐方式,以实现更精确的掌纹匹配。实验结果表明,该方法大大提高了掌纹识别的准确性,并且可以实时工作。

著录项

  • 作者

    Li W; Zhang B; Zhang L; Yan J;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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