2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics最新文献_第2页

Knuckle Biometrics Based on Texture Features 基于纹理特征的关节生物识别

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559285

M. Choraś, R. Kozik

引用次数: 26

A Comparative Study of Combining Multiple Features for Fingerprint Recognition 结合多特征进行指纹识别的比较研究

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559281

Fanglin Chen, Jie Zhou

{"title":"A Comparative Study of Combining Multiple Features for Fingerprint Recognition","authors":"Fanglin Chen, Jie Zhou","doi":"10.1109/ETCHB.2010.5559281","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559281","url":null,"abstract":"A number of different features, besides minutiae, have been used for fingerprint matching. There include orientation-based minutia descriptor, FingerCode, ridge feature map, orientation map, and density map. Previous studies have shown that the performance of a fingerprint recognition system can be improved by combining these features with minutiae through a fusion strategy. In this paper, a comparative study of combining multiple features is carried out on a large database. Based on the experimental results, some useful conclusions can be drawn: (1) A larger improvement can usually be obtained as we combine more features; (2) However, beyond 4 features, the performance improvement is very small. (3) MD (minutiae and orientation-based minutia descriptor) are the best of two-feature combinations. It is interesting that the single feature D (minutia descriptor) does not perform the best, but the combination of MD (minutiae and minutia descriptor) performs very well. (4) Although the combinations of MO and MD performs the best among the two-feature combinations, MDO performs not so good as MDR (minutiae, minutia descriptor, and ridge density map) due to the correlativeness between D and O. These observations are helpful for designing practical fingerprint matching systems.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"200 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":"122104836","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: 1

Analyzing Fingerprints of Indian Population Using Image Quality: A UIDAI Case Study 使用图像质量分析印度人口指纹:一个UIDAI案例研究

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559279

Mayank Vatsa, R. Singh, S. Bharadwaj, H. Bhatt, R. Mashruwala

引用次数: 17

Multispectral Palmprint Recognition Using Quaternion Principal Component Analysis 基于四元数主成分分析的多光谱掌纹识别

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559287

Xingpeng Xu, Zhenhua Guo

引用次数: 34

Hand-Based Biometrics Fusing Palmprint and Finger-Knuckle-Print 融合掌纹和指关节指纹的手部生物识别技术

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559284

L. Shen, L. Bai, Z. Ji

引用次数: 17

A Research on Feature Selection and Fusion in Palmprint Recognition 掌纹识别中的特征选择与融合研究

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559290

Caimao Yuan, Dongmei Sun, Di Liu, Siu-Yeung Cho, Yanqiang Zhang

{"title":"A Research on Feature Selection and Fusion in Palmprint Recognition","authors":"Caimao Yuan, Dongmei Sun, Di Liu, Siu-Yeung Cho, Yanqiang Zhang","doi":"10.1109/ETCHB.2010.5559290","DOIUrl":"https://doi.org/10.1109/ETCHB.2010.5559290","url":null,"abstract":"In the palmprint identification system, feature fusion has been emerging an effective way to improve system performance. Feature vectors extracted from palmprint and fusion strategy are key factors in this procedure. This paper discusses issues about the two aspects respectively. (1) The performance will decline considerably as the number of categories increase. This is determined by the intrinsic characteristics of the selected feature vectors. To overcome this problem, we propose a feature selection method based on K-L distance between feature vectors of each person and the population in each dimension. Experimental results show that the performance of the system keeps a stable level when the categories increase. (2) Whether the fusion of different feature vectors can bring improved performance, it depends on which feature vectors should be chosen. For feature level fusion (FLF), feature vectors should have weak correlation between each other. In this paper, we studied the correlation based on Spearman correlations coefficient. If the matrix reflects a strong correlation, this fusion strategy should be a failure. We test two fusion strategies in experiment. A) Feature vectors extracted by principle components analysis method (PCA) plus feature vectors extracted by PCA method from images after DCT transform. B) Feature vectors extracted by PCA method plus feature vectors extracted by independent components analysis (ICA) method. Experimental results show that strategy B brings an improved performance, for the features vectors in this strategy with weak correlation.","PeriodicalId":174704,"journal":{"name":"2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics","volume":"19 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":"128512391","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: 5

Combining Level-3 Features with Perspiration Pattern: Extended Database Results 结合三级特征与汗水模式:扩展数据库结果

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-08-30 DOI: 10.1109/ETCHB.2010.5559280

A. Abhyankar, S. Schuckers

引用次数: 1

Biometric Identification through Hand Vein Patterns 通过手部静脉模式进行生物识别

2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics Pub Date : 2010-04-22 DOI: 10.1109/SIU.2010.5652148

A. Yuksel, L. Akarun, B. Sankur

引用次数: 43