作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2010, Vol. 36 ›› Issue (18): 217-219. doi: 10.3969/j.issn.1000-3428.2010.18.075

• 人工智能及识别技术 • 上一篇    下一篇

渐进式虹膜图像质量评估模型

吕林涛,石富旬   

  1. (西安理工大学计算机科学与工程学院,西安 710048)
  • 出版日期:2010-09-20 发布日期:2010-09-30
  • 作者简介:吕林涛(1955-),男,教授,主研方向:网络信息安全,数据挖掘,虹膜识别;石富旬,硕士研究生
  • 基金资助:
    西安市2008年科学技术计划基金资助项目“嵌入式长距离虹膜识别系统”(CXY08017)

Progressive Iris Image Quality Evaluation Model

LV Lin-tao, SHI Fu-xun   

  1. (School of Computer Science & Engineering, Xi’an University of Techonloty, Xi’an 710048, China)
  • Online:2010-09-20 Published:2010-09-30

摘要: 虹膜图像质量评估目前尚无统一评估标准,导致虹膜识别拒识率和误识率较高。针对该问题,提出一种虹膜图像质量评估模型。根据虹膜图像中各干扰因素的不同特点,在先验知识基础上采用区域化、加权的方法,渐近式地实施像素级质量评估,依据像素级评估结果实施图像级质量评估。实验结果表明,像素级虹膜图像质量评估中的虹膜图像干扰项识别率和模糊识别率较高,图像级虹膜图像质量评估与人工评估结果相一致。

关键词: 虹膜图像, 图像质量评估, 虹膜识别

Abstract: Since there is no unified standard for iris image quality assessment at present, the recognition rejection rate and false acceptance rate cannot always be decreased efficiently. Aiming at this problem, this paper proposes a novel model for the assessment of iris image. According to the characteristics of different interfering factors in the iris image, regionalization and weighted methods are adopted on the basis of a prior knowledge in order to perform an incremental pixel-level evaluation of various interfering factors in iris images. The image-level overall evaluation based on pixel-level assessment results proceeds. Experimental results show that the pixel level iris image quality assessment has a better performance in blur recognition and interference term identification, image-level assessment of iris image quality assessment is consistent with the manual.

Key words: iris image, image quality evaluation, iris recognition

中图分类号: