Volume XLII-2/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 167-171, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-167-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 167-171, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-167-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 May 2019

09 May 2019

IRIS IMAGE KEY POINTS DESCRIPTORS BASED ON PHASE CONGRUENCY

M. А. Protsenko and E. A. Pavelyeva M. А. Protsenko and E. A. Pavelyeva
  • Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, 119991, Russia, Moscow, Leninskie Gory, MGU

Keywords: biometrics, iris recognition, key points, phase, phase congruency

Abstract. In this article the new method for iris image features extraction based on phase congruency is proposed. Iris image key points are calculated using the convolutions with Hermite transform functions. At each key point the feature vector characterizing this key point is obtained based on the phase congruency method. Iris key point descriptor contains phase congruency values at points located on concentric circles around the key point. To compare the key points, Euclidean metric between the key points descriptors is calculated. The distance between the iris images is equal to the number of matched iris key points. The proposed method was tested using the images from CASIA−IrisV4−Interval database and the value of EER = 0.226% was obtained.