李 杰,史艺丹,聂泽东,杨文耀,雷诗琪.手指静脉图像感兴趣区域快速提取方法研究[J].电子测量与仪器学报,2020,34(4):42-49
手指静脉图像感兴趣区域快速提取方法研究
Research on fast extraction method of region of interest in finger vein images
  
DOI:
中文关键词:  指静脉识别  感兴趣区域  快速提取  图像校正
英文关键词:finger vein recognition  region of interest  fast extraction  image correction
基金项目:重庆市自然科学基金面上项目(cstc2019jcyj-msxmX0824)、国家级大学生创新创业训练计划(201910642006)、重庆市教育委员会科学技术研究项目 ( KJQN201901304)、 重庆市博士后科研项目 ( Xm2017051 )、 重庆市高校新型储能器件及应用工程研究中心开放课题(KF20170204)、重庆文理学院校级科研项目(Z2018DQ01,R2016DQ11)资助
作者单位
李 杰 1. 重庆文理学院 新型储能器件及应用工程研究中心 
史艺丹 1. 重庆文理学院 新型储能器件及应用工程研究中心 
聂泽东 2. 中国科学院 深圳先进技术研究院 
杨文耀 1. 重庆文理学院 新型储能器件及应用工程研究中心 
雷诗琪 1. 重庆文理学院 新型储能器件及应用工程研究中心 
AuthorInstitution
Li Jie 1. Engineering Research Center of New Energy Storage Devices and Applications, Chongqing University of Arts and Sciences 
Shi Yidan 1. Engineering Research Center of New Energy Storage Devices and Applications, Chongqing University of Arts and Sciences 
Nie Zedong 2. Shenzhen Institutes of Advanced Technology, Chinese Academy of Science 
Yang Wenyao 1. Engineering Research Center of New Energy Storage Devices and Applications, Chongqing University of Arts and Sciences 
Lei Shiqi 1. Engineering Research Center of New Energy Storage Devices and Applications, Chongqing University of Arts and Sciences 
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中文摘要:
      手指静脉识别技术由于其非接触、高防伪性以及活体检测等优点,成为研究与应用的热点。 针对传统手指静脉图像感 兴趣区域提取方法过程复杂、运算量大的问题,提出一种感兴趣区域快速提取的方法。 该方法采用三点对比法定位手指上下边 界以及基于相似三角形定理的图像校正方法。 与传统的方法相比,省去了边缘优化的复杂过程以及减少了旋转校正的乘法运 算量,能将指静脉图像感兴趣区域提取的速度提高 2~ 3 倍。 利用指静脉图像库进行仿真实验,结果表明,本算法提取 ROI 的正 确率为 100%,识别的等错误率仅为 2. 45%,说明该方法具有较高的普适性和稳定性,能广泛应用在指静脉识别系统中。
英文摘要:
      Finger vein recognition technology has become a research and application hotspot due to its advantages of non-contact, high security and living body detection. In view of the complexity and large amount of computation of the traditional methods for extracting the region of interest (ROI) of finger vein images, a fast ROI extraction method was proposed. The method used a three-point comparison method to locate the upper and lower boundaries of the finger and an image correction method based on the similar triangle theorem. Compared with the traditional methods, the complex process of edge optimization was eliminated and the multiplication of rotation correction was reduced, and the speed of extracting the ROI of the finger vein images can be increased by 2 ~ 3 times. The finger vein image database was used for the simulation experiments, the results showed that the accuracy of this algorithm for extracting ROI was 100%, and the recognition equal error rate was only 2. 45%, which indicated that this method has high universality and stability and can be widely used in finger vein recognition.
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