China has long been a coal-based energyconsumption country.The coal's combustion process andits particle size are closely related.Because there are stilldifficulties in understanding and mastering the energyconsum...China has long been a coal-based energyconsumption country.The coal's combustion process andits particle size are closely related.Because there are stilldifficulties in understanding and mastering the energyconsumption of comminution,the economic fineness tobalance comminution and burning is mainly obtainedaccording to experience.With the increasingly wide andextensive use of coal,the energy consumption of coalcomminution has been paid more and more attention.Inthis paper,the research on energy consumption ofcomminution is analyzed and summarized to provide areference for the energy consumption of coalcomminution.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
文摘China has long been a coal-based energyconsumption country.The coal's combustion process andits particle size are closely related.Because there are stilldifficulties in understanding and mastering the energyconsumption of comminution,the economic fineness tobalance comminution and burning is mainly obtainedaccording to experience.With the increasingly wide andextensive use of coal,the energy consumption of coalcomminution has been paid more and more attention.Inthis paper,the research on energy consumption ofcomminution is analyzed and summarized to provide areference for the energy consumption of coalcomminution.
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.
