2018 International Workshop on Biometrics and Forensics (IWBF)最新文献_第2页

What can a single minutia tell about gender? 一个细枝末节能说明什么性别呢?

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401554

Philipp Terhörst, N. Damer, Andreas Braun, Arjan Kuijper

引用次数: 8

Use of creative materials for fingerprint spoofs 使用创造性的材料进行指纹欺骗

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401565

Ondrej Kanich, M. Drahanský, M. Mézl

引用次数: 12

Age and gender classification from ear images 耳朵图像的年龄和性别分类

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401568

Dogucan Yaman, Fevziye Irem Eyiokur, N. Sezgin, H. K. Ekenel

{"title":"Age and gender classification from ear images","authors":"Dogucan Yaman, Fevziye Irem Eyiokur, N. Sezgin, H. K. Ekenel","doi":"10.1109/IWBF.2018.8401568","DOIUrl":"https://doi.org/10.1109/IWBF.2018.8401568","url":null,"abstract":"In this paper, we present a detailed analysis on extracting soft biometrie traits, age and gender, from ear images. Although there have been a few previous work on gender classification using ear images, to the best of our knowledge, this study is the first work on age classification from ear images. In the study, we have utilized both geometric features and appearance-based features for ear representation. The utilized geometric features are based on eight anthropometric landmarks and consist of 14 distance measurements and two area calculations. The appearance-based methods employ deep convolutional neural networks for representation and classification. The well-known convolutional neural network models, namely, AlexNet, VGG-16, GoogLeNet, and SqueezeNet have been adopted for the study. They have been fine-tuned on a large-scale ear dataset that has been built from the profile and close-to-profile face images in the Multi-PIE face dataset. This way, we have performed a domain adaptation. The updated models have been fine-tuned once more time on the small-scale target ear dataset, which contains only around 270 ear images for training. According to the experimental results, appearance-based methods have been found to be superior to the methods based on geometric features. We have achieved 94% accuracy for gender classification, whereas 52% accuracy has been obtained for age classification. These results indicate that ear images provide useful cues for age and gender classification, however, further work is required for age estimation.","PeriodicalId":259849,"journal":{"name":"2018 International Workshop on Biometrics and Forensics (IWBF)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121372921","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: 21

Performance variation of morphed face image detection algorithms across different datasets 变形人脸图像检测算法在不同数据集上的性能变化

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401562

U. Scherhag, C. Rathgeb, C. Busch

引用次数: 29

PRNU-based detection of morphed face images 基于prnu的变形人脸图像检测

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401555

L. Debiasi, U. Scherhag, C. Rathgeb, A. Uhl, C. Busch

引用次数: 49

Fusion using neural networks for intoxication identification 融合神经网络用于中毒识别

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401556

G. Koukiou, V. Anastassopoulos

引用次数: 1

Impact of photometric transformations on PRNU estimation schemes: A case study using near infrared ocular images 光度变换对PRNU估计方案的影响:使用近红外眼图像的案例研究

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401560

Sudipta Banerjee, A. Ross

{"title":"Impact of photometric transformations on PRNU estimation schemes: A case study using near infrared ocular images","authors":"Sudipta Banerjee, A. Ross","doi":"10.1109/IWBF.2018.8401560","DOIUrl":"https://doi.org/10.1109/IWBF.2018.8401560","url":null,"abstract":"The principle of Photo Response Non Uniformity (PRNU) is often used to link a digital image with the sensor that produced it. In this regard, a number of schemes have been proposed in the literature to extract PRNU details from a given input image. In this work, we study the impact of photometric transformations applied to near-infrared ocular images, on PRNU-based iris sensor identification accuracy. The contributions of this work are as follows: (a) Firstly, we evaluate the impact of 7 different photometric transformations on 4 different PRNU-based sensor identification schemes; (b) Secondly, we develop an explanatory model based on the Jensen-Shannon divergence measure to analyze the conditions under which these PRNU estimation schemes fail on photometrically transformed images. The analysis is conducted using 9,626 ocular images pertaining to 11 different iris sensors. Experiments suggest that (a) the Enhanced Sensor Pattern Noise and Maximum Likelihood Estimation based Sensor Pattern Noise techniques are more robust to photometric transformations than other PRNU-based schemes; (b) the application of photometric transformations actually improves the performance of the Phase Sensor Pattern Noise scheme; (c) the single-scale Self Quotient Image (SQI) and Difference of Gaussians (DoG) filtering transformations adversely impact all 4 PRNU-based schemes considered in this work; and (d) the Jensen-Shannon divergence measure is able to explain the degradation in performance of PRNU-based schemes as a function of the photometrically modified images.","PeriodicalId":259849,"journal":{"name":"2018 International Workshop on Biometrics and Forensics (IWBF)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133406823","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: 7

Fast cross-correlation based wrist vein recognition algorithm with rotation and translation compensation 基于旋转和平移补偿的快速交叉相关腕静脉识别算法

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401550

O. Nikisins, Teodors Eglitis, André Anjos, S. Marcel

{"title":"Fast cross-correlation based wrist vein recognition algorithm with rotation and translation compensation","authors":"O. Nikisins, Teodors Eglitis, André Anjos, S. Marcel","doi":"10.1109/IWBF.2018.8401550","DOIUrl":"https://doi.org/10.1109/IWBF.2018.8401550","url":null,"abstract":"Most of the research on vein biometrics addresses the problems of either palm or finger vein recognition with a considerably smaller emphasis on wrist vein modality. This paper paves the way to a better understanding of capabilities and challenges in the field of wrist vein verification. This is achieved by introducing and discussing a fully automatic cross-correlation based wrist vein verification technique. Overcoming the limitations of ordinary cross-correlation, the proposed system is capable of compensating for scale, translation and rotation between vein patterns in a computationally efficient way. Introduced comparison algorithm requires only two cross-correlation operations to compensate for both translation and rotation, moreover the well known property of log-polar transformation of Fourier magnitudes is not involved in any form. To emphasize the veins, a two-layer Hessian-based vein enhancement approach with adaptive brightness normalization is introduced, improving the connectivity and the stability of extracted vein patterns. The experiments on the publicly available PUT Vein wrist database give promising results with FNMR of 3.75% for FMR « 0.1%. In addition we make this research reproducible providing the source code and instructions to replicate all findings in this work.","PeriodicalId":259849,"journal":{"name":"2018 International Workshop on Biometrics and Forensics (IWBF)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134643054","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

Data-driven segmentation of post-mortem iris images 数据驱动的死后虹膜图像分割

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401558

Mateusz Trokielewicz, A. Czajka

{"title":"Data-driven segmentation of post-mortem iris images","authors":"Mateusz Trokielewicz, A. Czajka","doi":"10.1109/IWBF.2018.8401558","DOIUrl":"https://doi.org/10.1109/IWBF.2018.8401558","url":null,"abstract":"This paper presents a method for segmenting iris images obtained from the deceased subjects, by training a deep convolutional neural network (DCNN) designed for the purpose of semantic segmentation. Post-mortem iris recognition has recently emerged as an alternative, or additional, method useful in forensic analysis. At the same time it poses many new challenges from the technological standpoint, one of them being the image segmentation stage, which has proven difficult to be reliably executed by conventional iris recognition methods. Our approach is based on the SegNet architecture, fine-tuned with 1,300 manually segmented post-mortem iris images taken from the Warsaw-BioBase-Post-Mortem-Iris v1.0 database. The experiments presented in this paper show that this data-driven solution is able to learn specific deformations present in post-mortem samples, which are missing from alive irises, and offers a considerable improvement over the state-of-the-art, conventional segmentation algorithm (OSIRIS): the Intersection over Union (IoU) metric was improved from 73.6% (for OSIRIS) to 83% (for DCNN-based presented in this paper) averaged over subject-disjoint, multiple splits of the data into train and test subsets. This paper offers the first known to us method of automatic processing of post-mortem iris images. We offer source codes with the trained DCNN that perform end-to-end segmentation of post-mortem iris images, as described in this paper. Also, we offer binary masks corresponding to manual segmentation of samples from Warsaw-BioBase-Post-Mortem-Iris v1.0 database to facilitate development of alternative methods for post-mortem iris segmentation.","PeriodicalId":259849,"journal":{"name":"2018 International Workshop on Biometrics and Forensics (IWBF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130910901","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: 16

Face recognition “on the move” combining incomplete information 人脸识别“移动中”结合不完整信息

2018 International Workshop on Biometrics and Forensics (IWBF) Pub Date : 2018-06-01 DOI: 10.1109/IWBF.2018.8401559

Souad Khellat-Kihel, A. Lagorio, M. Tistarelli

引用次数: 1