《计算机应用研究》|Application Research of Computers

改进的单幅近红外掌纹掌静脉图像融合识别

Improved fusion recognition for near infrared palmprint and palm vein image

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作者 江晓龙,王华彬,王东旭,朱颜,陶亮
机构 安徽大学 计算机科学与技术学院,合肥 230601
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文章编号 1001-3695(2019)06-063-1901-06
DOI 10.19734/j.issn.1001-3695.2018.01.0055
摘要 现有的单幅近红外掌静脉掌纹融合识别算法不能很好地突出掌纹与掌静脉结构。针对这个问题,提出一种改进的融合识别算法。采用分块模型去除图像中的掌静脉得到掌纹结构,通过隶属度函数对掌纹结构进行模糊化,再进行反锐化掩模增强,突出掌纹结构信息。使用边缘检测加权引导滤波对掌静脉结构进行增强,突出掌静脉结构,将掌纹与掌静脉图像进行融合。实验结果表明,改进后的融合识别算法的识别率达到了99.81%。
关键词 掌纹; 掌静脉; 融合识别; 隶属度函数; 模糊化; 反锐化掩模
基金项目 国家自然科学基金资助项目(61372137)
安徽大学大学生创新创业项目(CXCY2016313)
本文URL http://www.arocmag.com/article/01-2019-06-063.html
英文标题 Improved fusion recognition for near infrared palmprint and palm vein image
作者英文名 Jiang Xiaolong, Wang Huabin, Wang Dongxu, Zhu Yan, Tao Liang
机构英文名 School of Computer Science & Technology,Anhui University,Hefei 230601,China
英文摘要 The palmprint enhancement algorithm and the palm vein enhancement algorithm in single near infrared palm vein palmprint fusion recognition algorithm can not highlight the palmprint structure and palm vein structure well. To solve this problem, this paper proposed an improved palmprint and palm vein fusion algorithm. First, it used the block model to remove the palm to get the structure of the pure palmprint, and defined a new membership function to make palmprint structure fuzzified, then it combined the fuzzy palmprint structure with the anti-sharpening mask method to highlight the palmprint structure information. Secondly, it used edge detection weighted guided filtering to enhance the structure of the palm vein so that the palm vein structure was highlighted. Finally, it acquired the palmprint and palm vein images for adaptive weight fusion. The experimental results show that the recognition rate of the improved fusion recognition algorithm reaches 99.81%.
英文关键词 palmprint; palm vein; fusion recognition; membership function; fuzzification; anti-sharpening mask
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收稿日期 2018/1/11
修回日期 2018/3/7
页码 1901-1906
中图分类号 TP391.4;TP301.6
文献标志码 A