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2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics最新文献

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A Comparative Study of Hand Recognition Systems 手识别系统的比较研究
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559278
G. Amayeh, G. Bebis, M. Hussain
{"title":"A Comparative Study of Hand Recognition Systems","authors":"G. Amayeh, G. Bebis, M. Hussain","doi":"10.1109/ETCHB.2010.5559278","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559278","url":null,"abstract":"Hand-based recognition represents a key biometric technology with a wide range of potential applications both in industry and government. By far, many different handbased recognition algorithms have been developed. This paper presents a comparative study to evaluate the performance of three state of the art hand-based recognition methods. Using the University of Nevada at Reno (UNR) and the University of Notre Dame (UND) hand databases, we compare a geometricbased method, a component-based approach using Zernike moments, and an algorithm employing 3D finger surface features. Both recognition and authentication experiments have been conducted to investigate the performance and robustness of the three methods. Our experimental results show that Zernike descriptors yield features that are more robust and accurate compared to hand geometric features and 3D finger surface features.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123737805","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
Finger Vein Recognition Algorithm Using Phase Only Correlation 基于相位相关的手指静脉识别算法
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559283
Nurhafizah Mahri, Shahrel Azmin Sundi Suandi, B. A. Rosdi
{"title":"Finger Vein Recognition Algorithm Using Phase Only Correlation","authors":"Nurhafizah Mahri, Shahrel Azmin Sundi Suandi, B. A. Rosdi","doi":"10.1109/ETCHB.2010.5559283","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559283","url":null,"abstract":"In this paper, we propose an algorithm for finger vein recognition with less complexity in the image preprocessing phase, where finger vein pattern extraction is not included at all. In the proposed algorithm, we implement phase-only correlation (POC) function at the matching stage with a very simple preprocessing technique. Experimental evaluation of the proposed algorithm using a set of finger vein images captured from a low cost device have resulting an efficient recognition performance where the equal error rate (EER) was 0.9803% with a total processing time of 0.6362s.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129896351","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: 56
Detecting Invalid Samples in Hand Geometry Verification through Geometric Measurements 通过几何测量检测手部几何验证中的无效样本
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559296
Javier Burgués, Julian Fierrez, D. Ramos, Maria Puertas, J. Ortega-Garcia
{"title":"Detecting Invalid Samples in Hand Geometry Verification through Geometric Measurements","authors":"Javier Burgués, Julian Fierrez, D. Ramos, Maria Puertas, J. Ortega-Garcia","doi":"10.1109/ETCHB.2010.5559296","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559296","url":null,"abstract":"The performance of an automatic hand geometry authentication system relies heavily on the quality of the captured hand images. Factors related to the acquisition device (e.g. dirty scanner surface) or the usersensor interaction process (e.g. hand positioning) can degrade the quality of the acquired sample. Therefore, upon capture of a hand sample it is important to assess its validity. In this paper, an invalid sample detection module based on geometric constraints is presented. The experimental setup consists of a hand geometry verification system tested in two different acquisition scenarios: BiosecurID (400 users, scanner) and Biosecure (210 users, camera). Results confirm a noticeable improvement in the system performance as the fraction of nvalid samples rejected increases. In particular, discarding about 5 percent of the images in BiosecurID produces an improvement from 2.8 % EER to 0.1 % EER.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114218783","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: 6
Palmprint Recognition Using Kernel Spectral Regression Discriminant Analysis and HOG Representation 基于核谱回归判别分析和HOG表示的掌纹识别
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559288
Wei Jia, Jie Gui, Rongxiang Hu, Ying-Ke Lei
{"title":"Palmprint Recognition Using Kernel Spectral Regression Discriminant Analysis and HOG Representation","authors":"Wei Jia, Jie Gui, Rongxiang Hu, Ying-Ke Lei","doi":"10.1109/ETCHB.2010.5559288","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559288","url":null,"abstract":"In this paper, we propose a new appearance based approach for palmprint recognition, which combines Kernel Spectral Regression Discriminant Analysis (KSRDA) method and HOG representation. KSRDA is the kernel version of SRDA which has lower computation complexity than Linear Discriminant Analysis (LDA). Meanwhile, HOG representation isn't sensitive to changes of illumination, and has the robustness against deformations because slight translations and rotations make small histogram value changes. As a result, the proposed approach can achieve promising recognition rate. The results of experiments conducted on Hong Kong Polytechnic University Palmprint Database II and the blue band of Hong Kong Polytechnic University Multispectral Palmprint Database demonstrate the effectiveness of proposed approach.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114336976","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: 3
Multispectral Palm Image Fusion for Person Authentication Using Ant Colony Optimization 基于蚁群优化的手掌多光谱图像融合
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559292
D. Kisku, Phalguni Gupta, J. Sing, C. Jinshong Hwang
{"title":"Multispectral Palm Image Fusion for Person Authentication Using Ant Colony Optimization","authors":"D. Kisku, Phalguni Gupta, J. Sing, C. Jinshong Hwang","doi":"10.1109/ETCHB.2010.5559292","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559292","url":null,"abstract":"This paper presents an intra-modal fusion environment to integrate multiple raw palm images at low level. Fusion of palmprint instances is performed by wavelet transform and decomposition. To capture the palm characteristics, fused image is convolved with Gabor wavelet transform. The Gabor wavelet feature representation reflects very high dimensional space. To reduce the high dimensionality, ant colony optimization algorithm is applied to select relevant, distinctive and reduced feature set from Gabor responses. Finally, the reduced set of features is trained with support vector machines and accomplished user recognition tasks. For evaluation, CASIA multispectral palmprint database is used. The experimental results reveal that the system is found to be robust and encouraging while variations of classifiers are used. Also a comparative study is presented of the proposed system with a well-known method.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128687381","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: 20
MonogenicCode: A Novel Fast Feature Coding Algorithm with Applications to Finger-Knuckle-Print Recognition 单基因编码:一种新的快速特征编码算法及其在指关节指纹识别中的应用
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559286
Lin Zhang, Lei Zhang, David Zhang
{"title":"MonogenicCode: A Novel Fast Feature Coding Algorithm with Applications to Finger-Knuckle-Print Recognition","authors":"Lin Zhang, Lei Zhang, David Zhang","doi":"10.1109/ETCHB.2010.5559286","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559286","url":null,"abstract":"Biometrics based personal authentication is an effective method for recognizing a person's identity. Recently, it is found that the finger-knuckle-print (FKP), which refers to the inherent skin patterns of the outer surface around the phalangeal joint of one's finger, can serve as a distinctive biometric identifier. In this paper, a novel feature extraction and coding method, namely MonogenicCode, is presented based on the monogenic signal theory, and is applied to FKP recognition. For each image pixel, the associated MonogenicCode is a 3-bits vector obtained by binarizing the monogenic signal at this position, and it can reflect the local phase and orientation information at that position. Experiments conducted on our established FKP database indicate that this new method achieves competitive verification accuracy with state-of-the-art methods, while it needs the least time for feature extraction, making it the best choice for real-time applications.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132744185","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: 48
Weighted Linear Embedding and Its Applications to Finger-Knuckle-Print and Palmprint Recognition 加权线性嵌入及其在指关节指纹和掌纹识别中的应用
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559291
Jun Yin, Jingbo Zhou, Zhong Jin, Jian Yang
{"title":"Weighted Linear Embedding and Its Applications to Finger-Knuckle-Print and Palmprint Recognition","authors":"Jun Yin, Jingbo Zhou, Zhong Jin, Jian Yang","doi":"10.1109/ETCHB.2010.5559291","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559291","url":null,"abstract":"In this paper we propose a new linear feature extraction approach called Weighted Linear Embedding (WLE). WLE combines Fisher criterion with manifold learning criterion like local discriminant embedding analysis (LDE), whereas unlike LDE that only utilizes local neighbor information it uses local information and nonlocal information simultaneously. WLE is also unlike linear discriminant analysis (LDA) that treats local information and nonlocal information equally, and it uses these two kinds of information discriminatively by utilizing the Gaussian weighting. Hence, WLE is more powerful than LDA and LDE for feature extraction. Experimental results on the PolyU finger-knuckle-print database and the PolyU palmprint database indicate that our WLE algorithm outperforms principal components analysis (PCA), LDA and LDE.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127806986","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
Hand Biometric Segmentation by Means of Fuzzy Multiscale Aggregation for Mobile Devices 基于模糊多尺度聚合的移动设备手部生物特征分割
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559293
Ángel García-Casarrubios Muñoz, A. de Santos Sierra, C. S. Ávila, J. Casanova, Gonzalo Bailador del Pozo, V. J. Vera
{"title":"Hand Biometric Segmentation by Means of Fuzzy Multiscale Aggregation for Mobile Devices","authors":"Ángel García-Casarrubios Muñoz, A. de Santos Sierra, C. S. Ávila, J. Casanova, Gonzalo Bailador del Pozo, V. J. Vera","doi":"10.1109/ETCHB.2010.5559293","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559293","url":null,"abstract":"Biometrics applied to mobile devices is one of the most recent topic of interest in biometrics. Due to the limitations of these devices, in terms of computational cost, biometric techniques must be carefully adapted to this architectures. This paper proposes a quasi-linear approach for hand biometric segmentation based on fuzzy multiscale aggregation. The algorithm yields promising results in terms of segmentation accuracy, being tested with hand images acquired with a mobile device in a non-controlled and non-invasive environment. Finally, this approach is compared to the performance of the well-known Normalized Cuts algorithm, with positive results.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130784516","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
Hand-Based Feature Level Fusion for Single Sample Biometrics Recognition 单样本生物特征识别的手部特征融合
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559289
Yanqiang Zhang, Dongmei Sun, Z. Qiu
{"title":"Hand-Based Feature Level Fusion for Single Sample Biometrics Recognition","authors":"Yanqiang Zhang, Dongmei Sun, Z. Qiu","doi":"10.1109/ETCHB.2010.5559289","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559289","url":null,"abstract":"Single sample biometrics recognition may lead to bad recognition result in real-world applications. To solve this problem, we present a novel feature level biometrics fusion approach by combining two kinds of biometrics: palmprint and middle finger image, both of which can be acquired from one hand image. We first utilize a manifold learning method to find the local embedding subspaces of palmprint and middle finger images, and then use principal component analysis (PCA) to extract the concatenated feature. To do so, a well performance could be obtained for the reason that the local structures of single model biometrics are preserved, while the redundancies between them are reduced. Comparing with single modal biometrics and score level fusion, the experimental results illustrated the average recognition rate of the proposed approach was significantly promoted to 98.71%. The performance comparisons in terms of cumulative match characteristic (CMC) curves for different recognition approaches were also presented to demonstrate the strength of the proposed fusion scheme.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130824520","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: 28
Directional Energy Based Feature Level Multimodal System Using Palm and Fingerprints 基于手掌和指纹的定向能量特征级多模态系统
2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559282
Salah ud-Din, A. Mansoor, Mustafa Mumtaz, Hassan Masood
{"title":"Directional Energy Based Feature Level Multimodal System Using Palm and Fingerprints","authors":"Salah ud-Din, A. Mansoor, Mustafa Mumtaz, Hassan Masood","doi":"10.1109/ETCHB.2010.5559282","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559282","url":null,"abstract":"The ever increasing demand of security has resulted in wide use of Biometric systems. Despite overcoming the traditional verification problems, the unimodal systems suffer from various challenges like intra class variation, noise in the sensor data etc, affecting the system performance. These problems are effectively handled by multimodal systems. In this paper, we present a feature level fused multimodal approach using palm and finger prints. Directional energy based feature vectors of palm and fingerprint identifiers are combined to form joint feature vector that is subsequently used to identify the individual using a distance classifier. The proposed multimodal system is tested on a developed database consisting of 440 palm and finger prints each of 55 individuals. Receiver Operating Characteristics curves are formed for unimodal and multimodal systems. Equal Error Rate (EER) of 0.538% for multimodal system depicts improved performance compared to 2.822% and 2.553% of palm and finger prints identifiers respectively.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124061538","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: 2
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