2017 5th International Workshop on Biometrics and Forensics (IWBF)最新文献

Self Geometric Relationship-based matching for palmprint identification using SIFT 基于自几何关系匹配的SIFT掌纹识别

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-05-29 DOI: 10.1109/IWBF.2017.7935093

Jumma Alamghtuf, F. Khelifi

引用次数: 2

Manually annotated characteristic descriptors: Measurability and variability 手动注释的特征描述符:可测量性和可变性

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-05-26 DOI: 10.1109/IWBF.2017.7935095

C. Zeinstra, R. Veldhuis, L. Spreeuwers, A. Ruifrok

引用次数: 1

Random sampling for patch-based face recognition 基于补丁的随机采样人脸识别

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-05 DOI: 10.1109/IWBF.2017.7935104

Ismahane Cheheb, Noor Al-Máadeed, S. Al-Maadeed, A. Bouridane, Richard M. Jiang

引用次数: 20

Reversible data hiding in encrypted images using reformed JPEG compression 可逆数据隐藏在加密图像使用改革后的JPEG压缩

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935100

Xiao-zhu Xie, Chinchen Chang

引用次数: 9

Reversible data hiding in JPEG images based on adjustable padding 基于可调填充的JPEG图像中的可逆数据隐藏

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935083

Ching-Chun Chang, Chang-Tsun Li

引用次数: 7

From image to sensor: Comparative evaluation of multiple PRNU estimation schemes for identifying sensors from NIR iris images 从图像到传感器:从近红外虹膜图像中识别传感器的多个PRNU估计方案的比较评估

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935081

Sudipta Banerjee, A. Ross

{"title":"From image to sensor: Comparative evaluation of multiple PRNU estimation schemes for identifying sensors from NIR iris images","authors":"Sudipta Banerjee, A. Ross","doi":"10.1109/IWBF.2017.7935081","DOIUrl":"https://doi.org/10.1109/IWBF.2017.7935081","url":null,"abstract":"The field of digital image forensics concerns itself with the task of validating the authenticity of an image or determining the device that produced the image. Device or sensor identification can be accomplished by estimating sensor-specific pixel artifacts, such as Photo Response Non Uniformity (PRNU), that leave an imprint in the resulting image. Research in this field has predominantly focused on images obtained using sensors operating in the visible spectrum. Iris recognition systems, on the other hand, utilize sensors operating in the near-infrared (NIR) spectrum. In this work, we evaluate the applicability of different PRNU estimation schemes in accurately deducing sensor information from NIR iris images. We also analyze the impact of a photometric transformation on the estimation process. Experiments involving 12 sensors and 9511 images convey that the Basic and Enhanced Sensor Pattern Noise (SPN) schemes outperform the Maximum Likelihood and Phase-based SPN methods. Experiments also convey the need to explore alternate methods for performing digital image forensics on NIR iris images.","PeriodicalId":111316,"journal":{"name":"2017 5th International Workshop on Biometrics and Forensics (IWBF)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129144509","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: 10

Benchmarking face morphing forgery detection: Application of stirtrace for impact simulation of different processing steps 基准人脸变形伪造检测:stirtrace在不同处理步骤冲击仿真中的应用

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935087

M. Hildebrandt, T. Neubert, A. Makrushin, J. Dittmann

引用次数: 47

Predicting political mood tendencies based on Twitter data 根据Twitter数据预测政治情绪倾向

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935106

Aldo Hernandez-Suarez, G. Sánchez-Pérez, V. Martínez-Hernández, H. Meana, K. Toscano-Medina, M. Nakano-Miyatake, Victor Sanchez

引用次数: 13

Integrating facial makeup detection into multimodal biometric user verification system 将面部彩妆检测集成到多模态生物识别用户验证系统中

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935101

Ekberjan Derman, Chiara Galdi, J. Dugelay

{"title":"Integrating facial makeup detection into multimodal biometric user verification system","authors":"Ekberjan Derman, Chiara Galdi, J. Dugelay","doi":"10.1109/IWBF.2017.7935101","DOIUrl":"https://doi.org/10.1109/IWBF.2017.7935101","url":null,"abstract":"Multimodal biometric fusion is generally used for increasing the verification accuracy by combining two or more biometric traits. Fusion systems with predefined constant weight values for each biometry becomes much popular. Among biometrics, face modality is one of the most common traits that is used in such fusion system. However, face verification suffers from many challenging difficulties, one of which is facial makeup. Recently, it has been shown that the accuracy of face verification can be impacted by the presence of facial makeup. And as such, the verification result of a multimodal fusion system with constant weight value for each biometry can be degraded by facial cosmetics. In this work, we propose a method of integrating facial makeup detection into the fusion system to increase performance. In our investigated scenario, score level fusion of face, fingerprint and iris verification are performed, while the weight value of each trait changes dynamically according to the level of makeup classification of test facial image. So far, this is the first work taking into account the facial makeup within a multimodal biometric verification system. Experiments on 1600 different subjects reveal that our proposed method can help in increasing the overall performance of fusion system than without using the facial makeup information.","PeriodicalId":111316,"journal":{"name":"2017 5th International Workshop on Biometrics and Forensics (IWBF)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131198065","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: 4

Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging 人脸防欺骗对策:利用偏振成像对二维材料进行高效分类

2017 5th International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2017-04-04 DOI: 10.1109/IWBF.2017.7935105

A. Aziz, Hong Wei, J. Ferryman

{"title":"Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging","authors":"A. Aziz, Hong Wei, J. Ferryman","doi":"10.1109/IWBF.2017.7935105","DOIUrl":"https://doi.org/10.1109/IWBF.2017.7935105","url":null,"abstract":"Spoofing is an act to impersonate a valid user of any biometric systems in order to gain access. In a face biometric system, an imposter might use some fake masks that mimic the real user face. Existing countermeasures against spoofing adopt face texture analysis, motion detection and surface reflection analysis. For the purpose of face anti-spoofing analysis, skin structure is a key factor in achieving the target of our study. Skin consists of multiple layers structure which produces multiple reflections: surface and subsurface reflections. In this paper, we proposed a measure to discriminate between a genuine face and a printed paper photo based on physical properties of the materials which contribute to its distinctive reflection values. In order to differentiate the reflections, polarized light (light that vibrates in a single direction) can be used. The Stokes parameters are applied to generate the Stokes images which are then used to produce the final image known as Stokes degree of linear polarization (SDOLP) image. The intensity of the SDOLP image is investigated statistically which has shown promising results in the materials classification, between the skin and the paper mask. Furthermore, comparison between the experimental results from two skin color groups, black and others show that the SDOLP data distribution of black skin is similar to the printed paper photo of the same skin group.","PeriodicalId":111316,"journal":{"name":"2017 5th International Workshop on Biometrics and Forensics (IWBF)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114188524","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: 14