The relative distance of key point based iris recognition

Li Yu, Dapeng Zhang, Kuanquan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

68 Citations (Scopus)


Iris recognition has received increasing attention in recent years as a reliable approach to human identification. This paper makes an attempt to analyze the local feature structure of iris texture information based on the relative distance of key points. When preprocessed, the annular iris is normalized into a rectangular block. Multi-channel 2-D Gabor filters are used to capture the iris texture. In every filtered sub-image, we extract the points that can represent the local texture most effectively in each channel. The barycenter of these points in each channel is called the key point and a group of key points are obtained. Then, the distance between the center of key points of each sub-image and every key point is called relative distance, which is regarded as the iris feature vector. Iris feature matching is based on the Euclidean distance. Experimental results on public and private databases show that the performance of the proposed method is encouraging.
Original languageEnglish
Pages (from-to)423-430
Number of pages8
JournalPattern Recognition
Issue number2
Publication statusPublished - 1 Feb 2007


  • Gabor filter
  • Iris recognition
  • Key point
  • Relative distance

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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