2016 International Conference on Biometrics (ICB)最新文献

Latent fingerprint segmentation based on linear density 基于线性密度的潜在指纹分割

2016 International Conference on Biometrics (ICB) Pub Date : 2016-08-25 DOI: 10.1109/ICB.2016.7550076

Shuxin Liu, Manhua Liu, Zongyuang Yang

{"title":"Latent fingerprint segmentation based on linear density","authors":"Shuxin Liu, Manhua Liu, Zongyuang Yang","doi":"10.1109/ICB.2016.7550076","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550076","url":null,"abstract":"Latent fingerprints are the finger skin impressions left at the criminal scene unintentionally, which are important evidence for law enforcement agencies to identify criminals. Most of latent fingerprint images are of poor quality with unclear ridge structure and various non-fingerprint patterns. Segmentation is an important processing step to separate the fingerprint foreground from the background for more accurate and efficient feature extraction and identification. Traditional fingerprint segmentation methods are based on the information of gradients and local properties, which is sensitive to noise. This paper proposes a latent fingerprint segmentation algorithm based on linear density. First, a total variation (TV) image model is used to decompose a latent image into the cartoon and texture components. The texture component consisting of the latent fingerprint is used for further processing while the cartoon component is removed as noise. Second, we propose to detect a set of line segments from the texture image and compute the linear density map which can characterize the interleaved ridge and valley structure well. Finally, a segmentation mask is generated by thresholding the linear density map. The proposed method is tested on NIST SD27 latent fingerprint database. Experimental results and comparisons demonstrate the effectiveness of the proposed method.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114441964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Experimental results on multi-modal fusion of EEG-based personal verification algorithms 基于脑电图的多模态融合个人验证算法实验结果

2016 International Conference on Biometrics (ICB) Pub Date : 2016-08-25 DOI: 10.1109/ICB.2016.7550080

M. Garau, M. Fraschini, Luca Didaci, G. Marcialis

引用次数: 14

Compression standards in finger vein recognition 手指静脉识别中的压缩标准

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550046

Victoria Ablinger, C. Zenz, Jutta Hämmerle-Uhl, A. Uhl

引用次数: 4

Textured detailed graph model for dorsal hand vein recognition: A holistic approach 手背静脉识别的纹理精细图形模型:一种整体方法

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550047

Renke Zhang, Di Huang, Yunhong Wang

{"title":"Textured detailed graph model for dorsal hand vein recognition: A holistic approach","authors":"Renke Zhang, Di Huang, Yunhong Wang","doi":"10.1109/ICB.2016.7550047","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550047","url":null,"abstract":"Holistic- and local-based methods are two-pronged in dorsal hand vein recognition, and the latter ones have become dominant recently due to their advanced performance. In this paper, we propose a novel approach to dorsal hand vein recognition using a global graph model which takes both the texture and shape cues into account. We first extend the basic graph model consisting of the minutiae of the vein network and their connecting lines to a detailed one by increasing the number of vertices, describing the profile of the vein shape more accurately. We then append the holistic texture feature of the patch around each vertex, i.e. its PCA coefficients, to make the representation of the graph model more comprehensively. The above two steps significantly improve the discrimination of the graph model, and it reports the rank-one recognition rate of 98.82% on the NCUT dataset. This holistic result is comparable to the ones of most local based methods, demonstrating its effectiveness. Meanwhile, with local texture cues embedded, e.g. LBP, HOG, and Gabor, it further reaches the state of the art accuracy up to 99.22%, showing its good complementarity to local based methods.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129236997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Transferring deep representation for NIR-VIS heterogeneous face recognition NIR-VIS异构人脸识别的深度表征转移

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550064

Xiaoxiang Liu, Lingxiao Song, Xiang Wu, T. Tan

{"title":"Transferring deep representation for NIR-VIS heterogeneous face recognition","authors":"Xiaoxiang Liu, Lingxiao Song, Xiang Wu, T. Tan","doi":"10.1109/ICB.2016.7550064","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550064","url":null,"abstract":"One task of heterogeneous face recognition is to match a near infrared (NIR) face image to a visible light (VIS) image. In practice, there are often a few pairwise NIR-VIS face images but it is easy to collect lots of VIS face images. Therefore, how to use these unpaired VIS images to improve the NIR-VIS recognition accuracy is an ongoing issue. This paper presents a deep TransfeR NIR-VIS heterogeneous facE recognition neTwork (TRIVET) for NIR-VIS face recognition. First, to utilize large numbers of unpaired VIS face images, we employ the deep convolutional neural network (CNN) with ordinal measures to learn discriminative models. The ordinal activation function (Max-Feature-Map) is used to select discriminative features and make the models robust and lighten. Second, we transfer these models to NIR-VIS domain by fine-tuning with two types of NIR-VIS triplet loss. The triplet loss not only reduces intra-class NIR-VIS variations but also augments the number of positive training sample pairs. It makes fine-tuning deep models on a small dataset possible. The proposed method achieves state-of-the-art recognition performance on the most challenging CASIA NIR-VIS 2.0 Face Database. It achieves a new record on rank-1 accuracy of 95.74% and verification rate of 91.03% at FAR=0.001. It cuts the error rate in comparison with the best accuracy [27] by 69%.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114355363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 118

User individuality based cost-sensitive learning: A case study in finger vein recognition 基于用户个性的代价敏感学习:指静脉识别的案例研究

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550075

Lu Yang, Gongping Yang, Yilong Yin, Lizhen Zhou

{"title":"User individuality based cost-sensitive learning: A case study in finger vein recognition","authors":"Lu Yang, Gongping Yang, Yilong Yin, Lizhen Zhou","doi":"10.1109/ICB.2016.7550075","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550075","url":null,"abstract":"State-of-the-art cost-sensitive learning based techniques in biometrics ignore cost difference between users and determine the loss only based on the misrecognition category. In practice, this may not always hold and the user individuality may also affect the loss of misrecognition. For example, misrecognizing an imposter as an administrator can cause a much more serious loss than misrecognizing it as a normal user. At the same time, two administrators/normal users may have different probability to accept imposter. To confidently prevent the high-probability error, the cost of false acceptance for one user with a high probability should be larger than it for the other users. To make cost definition more reasonable and further lower misrecognition cost of a recognition system, we propose to incorporate the user individuality, i.e., user role and user gullibility, into the traditional cost-sensitive learning model through defining an improved object function. By employing the new model, we further develop a user role and gullibility based mckNN (rg-mckNN). Experimental results on finger vein databases demonstrate the effectiveness of the proposed method.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133293305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Discriminative Feature Adaptation for cross-domain facial expression recognition 基于特征自适应的跨域面部表情识别

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550085

Ronghang Zhu, Gaoli Sang, Qijun Zhao

{"title":"Discriminative Feature Adaptation for cross-domain facial expression recognition","authors":"Ronghang Zhu, Gaoli Sang, Qijun Zhao","doi":"10.1109/ICB.2016.7550085","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550085","url":null,"abstract":"Facial expression recognition is an important problem in many face-related tasks, such as face recognition, face animation, affective computing and human-computer interface. Existing methods mostly assume that testing and training face images are captured under the same condition and from the same population. Such assumption is, however, not valid in real-world applications, where face images could be taken from varying domains due to different cameras, illuminations, or populations. Motivated by recent progresses in domain adaptation, this paper proposes an unsupervised domain adaptation method, called discriminative feature adaptation (DFA), which requires for training a set of labelled face images in the source domain and some additional unlabelled face images in the target domain. It seeks for a feature space to represent face images from different domains such that two objectives are fulfilled: (i) mismatches between the feature distributions of these face images are minimized, and (ii) features are discriminative among these face images with respect to their facial expressions. Compared with existing methods, the proposed method can more effectively adapt discriminative features for recognizing facial expressions in various domains. Evaluation experiments have been done on four public facial expression databases: CK+, JAFFE, PICS, and FEED. The results demonstrate the superior performance of the proposed method over competing methods.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122081824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Post-mortem human iris recognition 人死后虹膜识别

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550073

Mateusz Trokielewicz, A. Czajka, P. Maciejewicz

{"title":"Post-mortem human iris recognition","authors":"Mateusz Trokielewicz, A. Czajka, P. Maciejewicz","doi":"10.1109/ICB.2016.7550073","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550073","url":null,"abstract":"This paper presents a unique analysis of post-mortem human iris recognition. Post-mortem human iris images were collected at the university mortuary in three sessions separated by approximately 11 hours, with the first session organized from 5 to 7 hours after demise. Analysis performed for four independent iris recognition methods shows that the common claim of the iris being useless for biometric identification soon after death is not entirely true. Since the pupil has a constant and neutral dilation after death (the so called “cadaveric position”), this makes the iris pattern perfectly visible from the standpoint of dilation. We found that more than 90% of irises are still correctly recognized when captured a few hours after death, and that serious iris deterioration begins approximately 22 hours later, since the recognition rate drops to a range of 13.3-73.3% (depending on the method used) when the cornea starts to be cloudy. There were only two failures to enroll (out of 104 images) observed for only a single method (out of four employed in this study). These findings show that the dynamics of post-mortem changes to the iris that are important for biometric identification are much more moderate than previously believed. To the best of our knowledge, this paper presents the first experimental study of how iris recognition works after death, and we hope that these preliminary findings will stimulate further research in this area.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126168197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 36

Exploring complementary features for iris recognition on mobile devices 探索虹膜识别在移动设备上的互补功能

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550079

Qi Zhang, Haiqing Li, Zhenan Sun, Zhaofeng He, T. Tan

引用次数: 21

Towards resolution invariant face recognition in uncontrolled scenarios 非受控场景下的分辨率不变人脸识别

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550087

Dan Zeng, Hu Chen, Qijun Zhao

引用次数: 31