IRIS IMAGE KEY POINTS DESCRIPTORS BASED ON PHASE CONGRUENCY

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Protsenko, M. А.^1¹ 

[1] Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, 119991, Russia, Moscow, Leninskie Gory, MGU^1

关键词: biometrics;    iris recognition;    key points;    phase;    phase congruency;   

DOI  :  10.5194/isprs-archives-XLII-2-W12-167-2019

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

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.

【 授权许可】

CC BY