DeepIris: Learning pairwise filter bank for heterogeneous iris verification

doi:10.1016/j.patrec.2015.09.016

CASIA OpenIR > 智能感知与计算研究中心

	DeepIris: Learning pairwise filter bank for heterogeneous iris verification
	Liu, Nianfeng; Zhang, Man; Li, Haiqing; Sun, Zhenan; Tan, Tieniu
发表期刊	PATTERN RECOGNITION LETTERS
	2016-10-15
卷号	82 期号:2 页码:154-161
文章类型	Article
摘要	Heterogeneous iris recognition (HIR) is in great demand for a large-scale identity management system. Iris images acquired in heterogeneous environment have large intra-class variations, such as different resolutions or different sensor optics, etc. Therefore, it is challenging to manually design a robust encoding filter to face the complex intra-class variations of heterogeneous iris images. This paper proposes a deep learning based framework for heterogeneous iris verification, namely DeepIris, which learns relational features to measure the similarity between pairs of iris images based on convolutional neural networks. DeepIris is a novel solution to iris recognition in two main aspects. (1) DeepIris learns a pairwise filter bank to establish the relationship between heterogeneous iris images, where pairs of filters are learned from two heterogeneous sources. (2) Different from two separate steps in terms of handcrafted feature extraction and feature matching in conventional solutions, DeepIris directly learns a nonlinear mapping function between pairs of iris images and their identity supervision with a pairwise filter bank (PFB) from different sources. Thus, the learned pairwise filters can adapt to new sources when given new training data. Extensive experimental results on the Q-FIRE and the CASIA cross sensor datasets demonstrate that EER (Equal Error Rate) of heterogeneous iris verification is reduced by 90% using DeepIris compared to traditional methods. (C) 2015 Elsevier B.V. All rights reserved.
关键词	Biometrics Iris Verification Convolutional Neural Networks Deep Learning Iris Recognition
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.patrec.2015.09.016
关键词[WOS]	IMAGES
收录类别	SCI
语种	英语
项目资助者	National Basic Research Program of China(2012CB316300) ; National Natural Science Foundation of China(61273272) ; Beijing Baidu Netcom Science Technology Co., Ltd.
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000386874600008
引用统计	被引频次：97[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13622
专题	智能感知与计算研究中心
作者单位	Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit,Inst Automat, Beijing, Peoples R China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Liu, Nianfeng,Zhang, Man,Li, Haiqing,et al. DeepIris: Learning pairwise filter bank for heterogeneous iris verification[J]. PATTERN RECOGNITION LETTERS,2016,82(2):154-161.
APA	Liu, Nianfeng,Zhang, Man,Li, Haiqing,Sun, Zhenan,&Tan, Tieniu.(2016).DeepIris: Learning pairwise filter bank for heterogeneous iris verification.PATTERN RECOGNITION LETTERS,82(2),154-161.
MLA	Liu, Nianfeng,et al."DeepIris: Learning pairwise filter bank for heterogeneous iris verification".PATTERN RECOGNITION LETTERS 82.2(2016):154-161.

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