基于融合像素点Gabor-Tetrolet的指关节纹识别

林森; 王媛

doi:10.37188/CJLCD.2021-0015

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基于融合像素点Gabor-Tetrolet的指关节纹识别

图像处理 | 更新时间：2021-09-10

- 基于融合像素点Gabor-Tetrolet的指关节纹识别
- Finger-knuckle-print recognition based on fused pixels Gabor-Tetrolet
- 液晶与显示 2021年36卷第9期页码：1314-1322
- 作者机构：
  
  1.沈阳理工大学自动化与电气工程学院, 辽宁沈阳 110159
  2.辽宁工程技术大学电子与信息工程学院, 辽宁葫芦岛 125105
- 作者简介：
  
  [ "林森(1980-), 男, 辽宁沈阳人, 博士, 副教授, 2013年于沈阳工业大学获得博士学位, 主要从事图像处理与模式识别方面的研究。E-mail:lin_sen6@126.com" ]
- 基金信息：
  
  国家重点研发计划(2018YFB1403303);辽宁省教育厅科学技术研究项目(LJ2019JL022);沈阳理工大学引进高层次人才科研支持计划(1010147000915)
- DOI：10.37188/CJLCD.2021-0015
  中图分类号： TP391.4
- 收稿日期：2021-01-14，
  
  修回日期：2021-02-06，
  
  纸质出版日期：2021-09
- 稿件说明：
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林森, 王媛. 基于融合像素点Gabor-Tetrolet的指关节纹识别[J]. 液晶与显示, 2021,36(9):1314-1322.

Sen LIN, Yuan WANG. Finger-knuckle-print recognition based on fused pixels Gabor-Tetrolet[J]. Chinese journal of liquid crystals and displays, 2021, 36(9): 1314-1322.
林森, 王媛. 基于融合像素点Gabor-Tetrolet的指关节纹识别[J]. 液晶与显示, 2021,36(9):1314-1322. DOI： 10.37188/CJLCD.2021-0015.

Sen LIN, Yuan WANG. Finger-knuckle-print recognition based on fused pixels Gabor-Tetrolet[J]. Chinese journal of liquid crystals and displays, 2021, 36(9): 1314-1322. DOI： 10.37188/CJLCD.2021-0015.

摘要

为了提取指关节纹图像的纹理特征并进一步提高其识别精度，提出一种基于改进Gabor小波和Tetrolet的指关节纹识别方法。首先，利用某点邻域像素的融合幅值特征代表该点的Gabor幅值特征，增强每个像素点之间的局部关联性；其次，将滤波后的指关节纹特征图像经过具有高稀疏性的Tetrolet变换以获取图像的最优稀疏表示；最后，利用带限相位相关（Band-Limited Phase-Only Correlation，BLPOC）算法提取指关节纹图像的互功率谱进行匹配。在PolyU-FK、PolyU-CFK、IITD图库得到的识别准确率分别为99.1300%，98.8324%，98.7937%，最低等误率为1.4601%，最短识别时间为0.043 2 s。本文方法能够提高识别系统的性能，具有可行性和有效性。

Abstract

In order to extract the texture features of finger-knuckle-print image and improve its recognition accuracy

a new method of finger-knuckle-print recognition based on improved Gabor wavelet and tetrolet is proposed. Firstly

the fused amplitude features of the neighboring pixels are used to represent the Gabor amplitude features of the point to enhance the local correlation between each pixel. Secondly

the filtered fingerprint feature image is transformed by tetrolet with high sparsity to obtain the optimal sparse representation of the image. Finally

band limited phase-only correlation is used to extract the cross power spectra of finger-knuckle-print image for matching. The correct recognition rate of PolyU-FK

PolyU-CFK and IITD database are 99.1300%

98.8324% and 98.7937%

respectively. The lowest equal error rate is 1.4601%

and the shortest recognition time is 0.043 2 s. The method proposed in this paper can improve the performance of the recognition system

and is feasible and effective.

关键词

Keywords

references

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