Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094349
Ruyi Zheng, Chao Zhang, Shihua He, Pengwei Hao
This paper addresses the problem of fast fingerprint retrieval in a large database using clustering-based descriptors. Common solutions fall into two categories: classification and indexing. However, those methods only use one form for space narrowing and neglecting the complementary uniqueness of classification and indexing. In addition, there are two major problems in fingerprint identification: partialness and non-linear distortion. Recently, many proposed features focus on global and minutia information and both of them can not deal well with those two problems. This paper has three contributions. First, it proposes a composite classification-indexing-retrieval framework that greatly reduces time complexity. Second, clustering-based descriptors are extracted for indexing so that the search space is narrowed largely. Third, the class-jumping principle (CJP) is proposed to determine the correctness of classification and handle the problem of misclassification.
{"title":"A Novel Composite Framework for Large-Scale Fingerprint Database Indexing and Fast Retrieval","authors":"Ruyi Zheng, Chao Zhang, Shihua He, Pengwei Hao","doi":"10.1109/ICHB.2011.6094349","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094349","url":null,"abstract":"This paper addresses the problem of fast fingerprint retrieval in a large database using clustering-based descriptors. Common solutions fall into two categories: classification and indexing. However, those methods only use one form for space narrowing and neglecting the complementary uniqueness of classification and indexing. In addition, there are two major problems in fingerprint identification: partialness and non-linear distortion. Recently, many proposed features focus on global and minutia information and both of them can not deal well with those two problems. This paper has three contributions. First, it proposes a composite classification-indexing-retrieval framework that greatly reduces time complexity. Second, clustering-based descriptors are extracted for indexing so that the search space is narrowed largely. Third, the class-jumping principle (CJP) is proposed to determine the correctness of classification and handle the problem of misclassification.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123217452","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094333
Kai Chen, David Zhang
In order to study the relationship between recognition performance of dorsal hand and spectra including visible and near-infrared light, a multispectral image capture system is established in this study, and it works well on the spectra with the wavelength from 520nm to 1040nm. The optimal band is considered to have the most effective features for recognition. Line feature extraction method is adopted regardless of the texture types. EER are calculated to reflect the differentiating ability across all bands after matching process. The spectrum of 880nm is testified to have the best performance of verification.
{"title":"Band Selection for Improvement of Dorsal Hand Recognition","authors":"Kai Chen, David Zhang","doi":"10.1109/ICHB.2011.6094333","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094333","url":null,"abstract":"In order to study the relationship between recognition performance of dorsal hand and spectra including visible and near-infrared light, a multispectral image capture system is established in this study, and it works well on the spectra with the wavelength from 520nm to 1040nm. The optimal band is considered to have the most effective features for recognition. Line feature extraction method is adopted regardless of the texture types. EER are calculated to reflect the differentiating ability across all bands after matching process. The spectrum of 880nm is testified to have the best performance of verification.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123552388","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094309
Marc Franzgrote, C. Borg, Benjamin J. Tobias Ries, S. Bussemaker, Xiaoyi Jiang, Michael Fieleser, Lei Zhang
With the rapid development of the mobile communication market the need for mobile biometrics emerges. This is a novel research topic within biometrics and not much work has been done in the past. This paper presents the initial work of a long-term project towards a robust mobile palmprint verification system. We develop a hand orientation normalization method which makes the palmprint acquisition on a mobile phone practical for casual use. The competitive code is adopted and accelerated for fast code matching. A performance study is performed on a dataset acquired using an iPhone. The achieved results provide a credible indication of the potential of palmprint verification in a mobile context and motivate further work.
{"title":"Palmprint Verification on Mobile Phones Using Accelerated Competitive Code","authors":"Marc Franzgrote, C. Borg, Benjamin J. Tobias Ries, S. Bussemaker, Xiaoyi Jiang, Michael Fieleser, Lei Zhang","doi":"10.1109/ICHB.2011.6094309","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094309","url":null,"abstract":"With the rapid development of the mobile communication market the need for mobile biometrics emerges. This is a novel research topic within biometrics and not much work has been done in the past. This paper presents the initial work of a long-term project towards a robust mobile palmprint verification system. We develop a hand orientation normalization method which makes the palmprint acquisition on a mobile phone practical for casual use. The competitive code is adopted and accelerated for fast code matching. A performance study is performed on a dataset acquired using an iPhone. The achieved results provide a credible indication of the potential of palmprint verification in a mobile context and motivate further work.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114267155","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094301
Yang Zhao, Wei Jia, Rongxiang Hu, Jie Gui
In this paper, a new Local Binary Pattern (LBP) and Local Ternary Pattern (LBP) based palmprint identification method is proposed. In our method, LBP or LTP descriptor is applied to the energy or direction representations of palmprint extracted by the modified finite radon transformation (MFRAT). Experimental results obtained from the Hong Kong Polytechnic University (PolyU) Palmprint Database demonstrate that the proposed method has higher identification rates than other LBP based methods.
{"title":"Palmprint Identification Using LBP and Different Representations","authors":"Yang Zhao, Wei Jia, Rongxiang Hu, Jie Gui","doi":"10.1109/ICHB.2011.6094301","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094301","url":null,"abstract":"In this paper, a new Local Binary Pattern (LBP) and Local Ternary Pattern (LBP) based palmprint identification method is proposed. In our method, LBP or LTP descriptor is applied to the energy or direction representations of palmprint extracted by the modified finite radon transformation (MFRAT). Experimental results obtained from the Hong Kong Polytechnic University (PolyU) Palmprint Database demonstrate that the proposed method has higher identification rates than other LBP based methods.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126789781","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094331
Yiding Wang, Kefeng Li, L. Shark, M. Varley
In this paper, a new feature descriptor is presented and proposed for personal verification based on near infrared images of hand-dorsa veins. This new feature descriptor is a modification of the previously proposed partition local binary patterns (PLBP) by adding feature weighting and error correction coding (ECC). While addition of feature weighting aims to reduce the influence of insignificant local binary patterns, addition of ECC aims to increase the distances between feature classes by utilizing the systematic redundancy that has been widely used to achieve reliable data transmission in noisy channels. Using a large database with more than two thousand hand-dorsa vein images, the resulting new feature descriptor, named Coded and Weighted PLBP (WCPLBP), is shown to be more effective than the original PLBP without feature weighting and ECC, and offers a better performance in recognition of hand-dorsa vein images with a correct recognition rate reaching approximately 99% using a simple nearest neighbor classifier.
{"title":"Hand-Dorsa Vein Recognition Based on Coded and Weighted Partition Local Binary Patterns","authors":"Yiding Wang, Kefeng Li, L. Shark, M. Varley","doi":"10.1109/ICHB.2011.6094331","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094331","url":null,"abstract":"In this paper, a new feature descriptor is presented and proposed for personal verification based on near infrared images of hand-dorsa veins. This new feature descriptor is a modification of the previously proposed partition local binary patterns (PLBP) by adding feature weighting and error correction coding (ECC). While addition of feature weighting aims to reduce the influence of insignificant local binary patterns, addition of ECC aims to increase the distances between feature classes by utilizing the systematic redundancy that has been widely used to achieve reliable data transmission in noisy channels. Using a large database with more than two thousand hand-dorsa vein images, the resulting new feature descriptor, named Coded and Weighted PLBP (WCPLBP), is shown to be more effective than the original PLBP without feature weighting and ECC, and offers a better performance in recognition of hand-dorsa vein images with a correct recognition rate reaching approximately 99% using a simple nearest neighbor classifier.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131263001","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094327
Xiaoyuan Jing, Wen-Qian Li, Chao Lan, Yong-Fang Yao, Xi Cheng, Lu Han
Manifold structure is important for a data set, and many subspace learning methods tend to preserve this structure in the learning process. In this paper, we simultaneously consider distances and angles between image data vectors to measure data similarities, in hope of more sufficiently capturing the manifold structure. In order to highlight the distinctions among angles between different data, and enhance the complementary information of angles compared with distance, we propose a new type of image angle measurement in a shifted image space that centered at the data mean. Both angle and distance are fused using the parallel fusion strategy, based on which we propose the complex locality preserving projections (CLPP) to extract low dimensional features that can better preserve the manifold structure of input data set. In order to remove redundant information among features, we further extend CLPP to the orthogonal complex locality preserving projections (OCLPP) approach, which produces orthogonal basis functions. Experimental results on PolyU finger-knuckle-print database show the effectiveness of our proposed approaches, which achieve better recognition performance compared with related mainfold-preserving learning methods.
{"title":"Orthogonal Complex Locality Preserving Projections Based on Image Space Metric for Finger-Knuckle-Print Recognition","authors":"Xiaoyuan Jing, Wen-Qian Li, Chao Lan, Yong-Fang Yao, Xi Cheng, Lu Han","doi":"10.1109/ICHB.2011.6094327","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094327","url":null,"abstract":"Manifold structure is important for a data set, and many subspace learning methods tend to preserve this structure in the learning process. In this paper, we simultaneously consider distances and angles between image data vectors to measure data similarities, in hope of more sufficiently capturing the manifold structure. In order to highlight the distinctions among angles between different data, and enhance the complementary information of angles compared with distance, we propose a new type of image angle measurement in a shifted image space that centered at the data mean. Both angle and distance are fused using the parallel fusion strategy, based on which we propose the complex locality preserving projections (CLPP) to extract low dimensional features that can better preserve the manifold structure of input data set. In order to remove redundant information among features, we further extend CLPP to the orthogonal complex locality preserving projections (OCLPP) approach, which produces orthogonal basis functions. Experimental results on PolyU finger-knuckle-print database show the effectiveness of our proposed approaches, which achieve better recognition performance compared with related mainfold-preserving learning methods.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114969128","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094336
Wei-qi Yuan, Yonghua Tang
Due to computer chip keys of the car and other purely electronic anti-theft means easy to be cracked, proposed to verify the legal identity of the user through dual-mode biometric based on palm print and palm vein, before launching vehicle. Ensure that it is very difficult to drive away the car without the agreement of the owner, even the car chip key cracked. According to vehicle characteristics, a two-way system structure is designed, which respectively to complete the image acquisition, parameter setting and transmission and the corresponding data processing and control, etc, in order to not destroy the appearance of the original structure, while adapting to limited space of the cab car.
{"title":"The Driver Authentication Device Based on the Characteristics of Palmprint and Palm Vein","authors":"Wei-qi Yuan, Yonghua Tang","doi":"10.1109/ICHB.2011.6094336","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094336","url":null,"abstract":"Due to computer chip keys of the car and other purely electronic anti-theft means easy to be cracked, proposed to verify the legal identity of the user through dual-mode biometric based on palm print and palm vein, before launching vehicle. Ensure that it is very difficult to drive away the car without the agreement of the owner, even the car chip key cracked. According to vehicle characteristics, a two-way system structure is designed, which respectively to complete the image acquisition, parameter setting and transmission and the corresponding data processing and control, etc, in order to not destroy the appearance of the original structure, while adapting to limited space of the cab car.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116308936","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094296
Bian Yang, C. Busch
We propose in this paper a keyed coding method to convert standardized fingerprint minutiae to randomized binary vectors. The geometric relationship among neighboring minutiae is encoded in a scalable way and thus the coding / comparison complexity and biometric performance can be adjusted through modifying the number of neighboring minutiae involved in score vector generation. Each encoded minutia has been self-aligned and has a binary form thus can be individually compared using Hamming distance in high efficiency. Key-controlled permutation and exclusive-or are used to gain diversifiability and security for the encoded minutiae template. Experimental results over the public database FVC2002DB2_A demonstrate high biometric performance by the proposed method. Besides the lightweight security achieved by the proposed method, the binary minutiae codes are easy to combine external cryptographic mechanisms and secure protocols for enhanced protection.
{"title":"Keyed Scalable Minutiae Coding","authors":"Bian Yang, C. Busch","doi":"10.1109/ICHB.2011.6094296","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094296","url":null,"abstract":"We propose in this paper a keyed coding method to convert standardized fingerprint minutiae to randomized binary vectors. The geometric relationship among neighboring minutiae is encoded in a scalable way and thus the coding / comparison complexity and biometric performance can be adjusted through modifying the number of neighboring minutiae involved in score vector generation. Each encoded minutia has been self-aligned and has a binary form thus can be individually compared using Hamming distance in high efficiency. Key-controlled permutation and exclusive-or are used to gain diversifiability and security for the encoded minutiae template. Experimental results over the public database FVC2002DB2_A demonstrate high biometric performance by the proposed method. Besides the lightweight security achieved by the proposed method, the binary minutiae codes are easy to combine external cryptographic mechanisms and secure protocols for enhanced protection.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132137679","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094303
Yong Xu, Qiong-xia Zhu
In this paper, we propose a PCA-based spectral band compression and multispectral palmprint recognition method. This method first exploits PCA to compress original multispectral bands to a smaller number of 'bands' and then uses the compressed bands to classify palmprint images. The experimental results show that our proposed PCA-based spectral band compression and recognition method can use very low-dimensional data to represent the original multispectral palmprint images and obtain a high classification accuracy.
{"title":"PCA-Based Multispectral Band Compression and Multispectral Palmprint Recognition","authors":"Yong Xu, Qiong-xia Zhu","doi":"10.1109/ICHB.2011.6094303","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094303","url":null,"abstract":"In this paper, we propose a PCA-based spectral band compression and multispectral palmprint recognition method. This method first exploits PCA to compress original multispectral bands to a smaller number of 'bands' and then uses the compressed bands to classify palmprint images. The experimental results show that our proposed PCA-based spectral band compression and recognition method can use very low-dimensional data to represent the original multispectral palmprint images and obtain a high classification accuracy.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131244799","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}
Pub Date : 2011-12-05DOI: 10.1109/ICHB.2011.6094300
Wei-qi Yuan, Seng-Fong Lin, Haibin Tong, Shudong Liu
A novel detection method of palmprint principal lines is proposed, which employs the priori knowledge of statistical properties about palm lines. Firstly, considering the particular direction of principal lines and the feature of their valley type edges, only one directional template of 45 degrees based on local minimum gray value is used to segment palmprint, and it can significantly reduce the excessive noise that multi-directional templates may bring. Next, a following method of the principal lines is employed, and another linking algorithm for the broken lines is devised. Compared with the existing methods, this scheme can limit principal lines detection in a small area, and trace the principal lines in a certain direction, thus it can effectively avoid the problem of blind searching and enhance the robustness. Finally, an index called "extraction rate"(ER) is defined to evaluate the effect of the proposed approach. The experiments based on the palmprint database of Hong Kong University of Science and Technology (HKUST) show that the extraction rate is 86.67%, and the principal lines are complete. Therefore this method can provide a good support for palmprint identification or other multimodal person identification.
{"title":"A Detection Method of Palmprint Principal Lines Based on Local Minimum Gray Value and Line Following","authors":"Wei-qi Yuan, Seng-Fong Lin, Haibin Tong, Shudong Liu","doi":"10.1109/ICHB.2011.6094300","DOIUrl":"https://doi.org/10.1109/ICHB.2011.6094300","url":null,"abstract":"A novel detection method of palmprint principal lines is proposed, which employs the priori knowledge of statistical properties about palm lines. Firstly, considering the particular direction of principal lines and the feature of their valley type edges, only one directional template of 45 degrees based on local minimum gray value is used to segment palmprint, and it can significantly reduce the excessive noise that multi-directional templates may bring. Next, a following method of the principal lines is employed, and another linking algorithm for the broken lines is devised. Compared with the existing methods, this scheme can limit principal lines detection in a small area, and trace the principal lines in a certain direction, thus it can effectively avoid the problem of blind searching and enhance the robustness. Finally, an index called \"extraction rate\"(ER) is defined to evaluate the effect of the proposed approach. The experiments based on the palmprint database of Hong Kong University of Science and Technology (HKUST) show that the extraction rate is 86.67%, and the principal lines are complete. Therefore this method can provide a good support for palmprint identification or other multimodal person identification.","PeriodicalId":378764,"journal":{"name":"2011 International Conference on Hand-Based Biometrics","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123271431","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：