Iris recognition based on Hilbert-Huang transform

Yang, Zhijing and Yang, Zhihua and Yang, Lihua (2009) Iris recognition based on Hilbert-Huang transform. Advances in Adaptive Data Analysis, 1 (4). pp. 623-641. ISSN 1793-5369

Documents
Iris_recognition_based_on_Hilbert-Huang_transform.pdf
[img]
[Download]
[img] PDF
Iris_recognition_based_on_Hilbert-Huang_transform.pdf - Whole Document
Restricted to Repository staff only

721Kb

Official URL: http://dx.doi.org/10.1142/S1793536909000291

Abstract

As a reliable approach for human identification, iris recognition has received increasing attention in recent years. This paper proposes a new analysis method for iris recognition based on Hilbert–Huang transform (HHT). We first divide a normalized iris image into several subregions. Then the main frequency center information ased on HHT of each subregion is employed to form the feature vector. The proposed iris recognition method has nice properties, such as translation invariance, scale invariance, rotation invariance, illumination invariance and robustness to high frequency noise. Moreover, the xperimental results on the CASIA iris database which is the largest publicly available iris image data sets show that the performance of the proposed method is encouraging and
comparable to the best iris recognition algorithm found in the current literature.

Item Type:Article
Additional Information:As a reliable approach for human identification, iris recognition has received increasing attention in recent years. This paper proposes a new analysis method for iris recognition based on Hilbert–Huang transform (HHT). We first divide a normalized iris image into several subregions. Then the main frequency center information ased on HHT of each subregion is employed to form the feature vector. The proposed iris recognition method has nice properties, such as translation invariance, scale invariance, rotation invariance, illumination invariance and robustness to high frequency noise. Moreover, the xperimental results on the CASIA iris database which is the largest publicly available iris image data sets show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.
Keywords:Iris recognition, empirical mode decomposition (EMD), Hilbert–Huang transform (HHT), main frequency center
Subjects:G Mathematical and Computer Sciences > G120 Applied Mathematics
Divisions:College of Science > School of Engineering
ID Code:4016
Deposited By:INVALID USER
Deposited On:13 Feb 2011 19:30
Last Modified:13 Mar 2013 08:55

Repository Staff Only: item control page