O438//D918.3 99053094指纹识别技术的发展=Development of fingerprintidentification teclnology[刊,中]/刘小华,王燕生(北京理工大学光电工程系.北京(100081))//光学技术.—1998,(4).—78—80对指纹识别技术的技术背景做了较为详细...O438//D918.3 99053094指纹识别技术的发展=Development of fingerprintidentification teclnology[刊,中]/刘小华,王燕生(北京理工大学光电工程系.北京(100081))//光学技术.—1998,(4).—78—80对指纹识别技术的技术背景做了较为详细的介绍,包括个人识别和特征识别、指纹识别及其优点、指纹识别的发展历史、其它识别办法的限制、指纹自动识别系统的发展现状等,然后对指纹识别技术的市场前景做了综述,包括指纹锁和指纹卡的潜在应用。总之,随着市场的推动和技术的提高,指纹识别应用领域将会越来越广泛,在人们生活中的作用也会越来越重要。(方舟)O438 99053095指纹图像小波压缩中子图信息的研究=Studies展开更多
Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent s...Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent series.First,fingerprint orientation flow field was obtained,using the gradient of fingerprint image.With these gradients,fingerprint orientation tensor field was calculated.Then,candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space.The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model.As a global descriptor,the Laurent polynomial coefficients were allowed for rotational invariance.Furthermore,a support vector machine(SVM)classifier was trained to remove spurious SPs,using cross-correlation coefficient as a feature vector.Finally,experiments were performed on Singular Point Detection Competition 2010(SPD2010)database.Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%,the accuracy of proposed algorithm is 45.34%.The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin,and the detection is invariant to rotational transformations.展开更多
基金Project(11JJ3080)supported by Natural Science Foundation of Hunan Province,ChinaProject(11CY012)supported by Cultivation in Hunan Colleges and Universities,ChinaProject(ET51007)supported by Youth Talent in Hunan University,China
文摘Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent series.First,fingerprint orientation flow field was obtained,using the gradient of fingerprint image.With these gradients,fingerprint orientation tensor field was calculated.Then,candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space.The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model.As a global descriptor,the Laurent polynomial coefficients were allowed for rotational invariance.Furthermore,a support vector machine(SVM)classifier was trained to remove spurious SPs,using cross-correlation coefficient as a feature vector.Finally,experiments were performed on Singular Point Detection Competition 2010(SPD2010)database.Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%,the accuracy of proposed algorithm is 45.34%.The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin,and the detection is invariant to rotational transformations.
