动态稀疏表示方法在非接触式指纹图像识别中的应用
DOI:
作者:
作者单位:

郑州大学西亚斯国际学院 电子信息工程学院

作者简介:

通讯作者:

中图分类号:

TP273

基金项目:

河南省教育厅研究项目(17A520017)


Application of Dynamic Sparse Representation in Non - contact Fingerprint Image Recognition
Author:
Affiliation:

Sias International University,School of Electronics and Information Engineering

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    传统指纹图像识别方法无法解决数据量大、样本维数高、样本数据呈非线性等问题。为此,将动态稀疏表示方法应用于非接触式指纹图像识别中。通过低秩矩阵恢复解决采集样本中出现的颜色偏差、局部遮挡以及内容缺失等问题。通过局部区域划分法把待识别图像分成若干子图像块,完成维数转换。引入可衡量待识别样本与训练样本间局部结构关系的准则和联合动态活跃集合对目标函数进行改进,建立动态稀疏表示模型。对各子图像的稀疏表示系数进行求解,依据稀疏表示系数求出所有非接触式指纹子图像的重构误差,融合全部误差,将误差最小的类别赋予待识别指纹图像,实现非接触式指纹图像识别。实验结果表明,所提方法实用性强,与其它方法相比识别可靠性更高。

    Abstract:

    The traditional fingerprint image recognition method can not solve the problems of large amount of data, high sample dimension and non-linear sample data. Therefore, the dynamic sparse representation method is applied to the non-contact fingerprint image recognition. The problem of color deviation, partial occlusion and content deletion in the collected samples is solved by the low-rank matrix recovery. By dividing the image to be subdivided into several sub-image blocks by the method of local area division, the dimension conversion is completed. This paper introduces the criterion that can measure the local structure of the sample to be identified and the training sample, and improves the objective function by combining the dynamic active set, and establishes the dynamic sparse representation model. The sparse representation coefficients of each sub-image are solved, all the reconstructed errors of the non-contact fingerprint sub-images are obtained according to the sparse representation coefficients, all the errors are merged, and the category with the smallest error is assigned to the fingerprint image to be identified to realize the non-contact fingerprint image Recognize. Experimental results show that the proposed method is practicable and more reliable than other methods.

    参考文献
    相似文献
    引证文献
引用本文

桑园. 动态稀疏表示方法在非接触式指纹图像识别中的应用[J]. 科学技术与工程, 2018, 18(21): .
Sang Yuan. Application of Dynamic Sparse Representation in Non - contact Fingerprint Image Recognition[J]. Science Technology and Engineering,2018,18(21).

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2017-12-26
  • 最后修改日期:2018-04-10
  • 录用日期:2018-04-18
  • 在线发布日期: 2018-07-30
  • 出版日期:
×
律回春渐,新元肇启|《科学技术与工程》编辑部恭祝新岁!
亟待确认版面费归属稿件,敬请作者关注