A novel iris segmentation using radial-suppression edge detection

Jing Huang, Xinge You*, Yuan Yan Tang, Liang Du, Yuan Yuan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Iris segmentation is a key step in the iris recognition system. The conventional methods of iris segmentation are based on the assumption that the inner and outer boundaries of an iris can be taken as circles. The region of the iris is segmented by detecting the circular inner and outer boundaries. However, we investigate the iris boundaries in the CASIA-IrisV3 database, and find that the actual iris boundaries are not always circular. In order to solve this problem, a new approach for iris segmentation based on radial-suppression edge detection is proposed in this paper. In the radial-suppression edge detection, a non-separable wavelet transform is used to extract the wavelet transform modulus of the iris image. Then, a new method of radial non-maxima suppression is proposed to retain the annular edges and simultaneously remove the radial edges. Next, a thresholding operation is utilized to remove the isolated edges and produce the final binary edge map. Based on the binary edge map, a self-adaptive method of iris boundary detection is proposed to produce final iris boundaries. Experimental results demonstrate that the proposed iris segmentation is desirable.

Original languageEnglish
Pages (from-to)2630-2643
Number of pages14
JournalSignal processing
Issue number12
Early online date9 May 2009
Publication statusPublished - Dec 2009


  • iris segmentation
  • non-separable wavelet transform
  • radial-suppression edge detection


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