2016 International Conference on Biometrics (ICB)最新文献_第2页

Single pulse ECG-based small scale user authentication using guided filtering 基于引导滤波的单脉冲ecg小规模用户认证

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550065

S. Chun

{"title":"Single pulse ECG-based small scale user authentication using guided filtering","authors":"S. Chun","doi":"10.1109/ICB.2016.7550065","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550065","url":null,"abstract":"Electrocardiogram (ECG) has been demonstrated as a promising biometric for user authentication or classification. However, most of the previous works on ECG biometrics dealt with more than five ECG pulses at once, which will require at least a few seconds to acquire. Moreover, many of them investigated classification systems that require ECG signals of many people for effective dimensionality reduction methods such as PCA or for powerful classifiers such as SVM. In this article, we consider fast responding, small scale authentication systems (e.g., wearable devices). We investigate the feasibility of using a single pulse ECG for authentication assuming that there is no access to others' ECG signals. Multiple ECG pulses are allowed only in the enrollment stage. We propose to use guided filter (GF) to reduce noise of a single ECG pulse using a low noise ECG template from the enrollment step. We employed simple distance measures such as Euclidean distance and dynamic time warping (DTW) for small scale authentication system and compared them with PCA based authentication system using others' ECG information. We evaluated our proposed methods with public ECGID database (89 subjects, selected 2 records per subject that were collected on the same day). Performance measures were used such as inter/intra distance ratio (IIDR), area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and equal error rate (EER). GF improved the performance of simple user authentication systems with Euclidean distance and DTW substantially. The Euclidean distance with GF achieved comparable authentication performance with PCA based method using other people's ECG information (EER = 2.4%).","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"358 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":"133644596","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: 26

Learning compact binary quantization of Minutia Cylinder Code 学习精细圆柱码的紧凑二进制量化

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550054

Chaochao Bai, Weiqiang Wang, T. Zhao, Mingqiang Li

引用次数: 5

Face recognition using scattering wavelet under Illicit Drug Abuse variations 基于散射小波的毒品变异人脸识别

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550091

Prateekshit Pandey, Richa Singh, Mayank Vatsa

引用次数: 30

Performance analysis of a Hybrid fingerprint extracted from optical coherence tomography fingertip scans 光学相干断层扫描指尖提取混合指纹的性能分析

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550045

L. N. Darlow, James Connan, Ann Singh

引用次数: 12

IrisSeg: A fast and robust iris segmentation framework for non-ideal iris images irissig:针对非理想虹膜图像的快速、鲁棒的虹膜分割框架

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550096

A. Gangwar, Akanksha Joshi, Ashutosh Singh, F. Alonso-Fernandez, J. Bigün

{"title":"IrisSeg: A fast and robust iris segmentation framework for non-ideal iris images","authors":"A. Gangwar, Akanksha Joshi, Ashutosh Singh, F. Alonso-Fernandez, J. Bigün","doi":"10.1109/ICB.2016.7550096","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550096","url":null,"abstract":"This paper presents a state-of-the-art iris segmentation framework specifically for non-ideal irises. The framework adopts coarse-to-fine strategy to localize different boundaries. In the approach, pupil is coarsely detected using an iterative search method exploiting dynamic thresholding and multiple local cues. The limbic boundary is first approximated in polar space using adaptive filters and then refined in Cartesian space. The framework is quite robust and unlike the previously reported works, does not require tuning of parameters for different databases. The segmentation accuracy (SA) is evaluated using well known measures; precision, recall and F-measure, using the publicly available ground truth data for challenging iris databases; CASIAV4-Interval, ND-IRIS-0405, and IITD. In addition, the approach is also evaluated on highly challenging periocular images of FOCS database. The validity of proposed framework is also ascertained by providing comprehensive comparisons with classical approaches as well as state-of-the-art methods such as; CAHT, WAHET, IFFP, GST and Osiris v4.1. The results demonstrate that our approach provides significant improvements in segmentation accuracy as well as in recognition performance that too with lower computational complexity.","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"23 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":"128334218","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: 46

Lock3DFace: A large-scale database of low-cost Kinect 3D faces Lock3DFace:一个大规模的低成本Kinect 3D人脸数据库

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550062

Jinjin Zhang, Di Huang, Yunhong Wang, Jia Sun

引用次数: 47

A study on the individuality of finger vein based on statistical analysis 基于统计分析的手指静脉个别性研究

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550089

Yapeng Ye, He Zheng, Liao Ni, Shilei Liu, Wenxin Li

引用次数: 10

Gender and ethnicity classification using deep learning in heterogeneous face recognition 基于深度学习的异质人脸识别中的性别和种族分类

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550082

Neeru Narang, T. Bourlai

{"title":"Gender and ethnicity classification using deep learning in heterogeneous face recognition","authors":"Neeru Narang, T. Bourlai","doi":"10.1109/ICB.2016.7550082","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550082","url":null,"abstract":"Although automated classification of soft biometric traits in terms of gender, ethnicity and age is a well-studied problem with a history of more than three decades, it is still far from being considered a solved problem for the case of difficult exposure conditions, such as during night-time, in environments with unconstrained lighting, or at large distances from the camera. In this paper, we investigate the advantages and limitations of the automated classification of soft biometric traits in terms of gender and ethnicity in Near-Infrared (NIR) long-range, night-time face images. The impact of soft biometric traits in terms of gender and ethnicity is explored for the purpose of improving cross-spectral face recognition (FR) performance. The main contributions are, (i) a dual database collected in NIR band at night time and at four different distances of 30, 60, 90 and 120 meters is used, (ii) a deep convolution neural network to perform the classification in terms of gender and ethnicity is proposed, (iii) a set of experiments is performed indicating that, the usage of soft biometric traits to perform face matching, resulted in a significantly improved rank-1 identification rate when compared to the original biometric system (scenario dependent).","PeriodicalId":308715,"journal":{"name":"2016 International Conference on Biometrics (ICB)","volume":"1 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":"130687119","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

Real world expression recognition: A highly imbalanced detection problem 真实世界的表情识别:一个高度不平衡的检测问题

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550074

Shan Li, Weihong Deng

引用次数: 6

TripleA: Accelerated accuracy-preserving alignment for iris-codes TripleA:加速虹膜编码的精度保持对齐

2016 International Conference on Biometrics (ICB) Pub Date : 2016-06-13 DOI: 10.1109/ICB.2016.7550063

C. Rathgeb, H. Hofbauer, A. Uhl, C. Busch

{"title":"TripleA: Accelerated accuracy-preserving alignment for iris-codes","authors":"C. Rathgeb, H. Hofbauer, A. Uhl, C. Busch","doi":"10.1109/ICB.2016.7550063","DOIUrl":"https://doi.org/10.1109/ICB.2016.7550063","url":null,"abstract":"The discriminative power of the iris enables reliable biometric recognition on large-scale databases where a rapid comparison of biometric reference data is essential to limit response times. In case of national-sized databases a one-to-many comparison might still represent a bottleneck of a biometric identification system, in particular if numerous relative tilt angles have to be considered in the comparisons stage. While a compensation of head tilts improves the robustness of an iris recognition system, extensive feature alignment increases the probability of a false match as well as comparison time. In this paper we present a novel method to accelerate iris biometric comparators in an accuracy-preserving way. Emphasis is put on the alignment of iris biometric reference data, i.e. iris-codes. Based on an analysis of the nature of iris-codes and comparison scores between them we propose an efficient two-step alignment process referred to as TripleA. This scheme, which can be operated in various modes, significantly reduces the amount of relative tilt angles to be considered during iris-code comparisons. Hence, comparison time as well as the probability of a false match are reduced at the same time. In an experimental evaluation on the Casia v4-Interval iris database we achieve a more than fourfold speed-up in the comparison stage maintaining biometric performance using different feature extraction techniques.","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":"114392438","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: 8