2009 International Conference on Information Technology and Computer Science 2009
DOI: 10.1109/itcs.2009.139 View full text |Buy / Rent full text
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“…For the feature fusion method, the best performance was achieved by the Weightedsum rule at 94.52% accuracy. The Average rule recognition rate was at 96.41% and the Product rule recognition rate was at 96.20% [15]. The combination of 2DPCA and LDA achieved a higher recognition rate of 94.4% [18].…”
Section: Resultsmentioning
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“…For the feature fusion method, the best performance was achieved by the Weightedsum rule at 94.52% accuracy. The Average rule recognition rate was at 96.41% and the Product rule recognition rate was at 96.20% [15]. The combination of 2DPCA and LDA achieved a higher recognition rate of 94.4% [18].…”
Section: Resultsmentioning
“…The kernel based non-intrusive fusion of ear and face features were obtained by utilizing connection relationship [15,19]. To achieve the rights management of digital content with large population coverage, watermarking algorithm was used.…”
Section: I) Fusion At Feature Extraction Levelmentioning
“…Table 1 sums up the various highlights of multi-modular biometric considers. Xu Xiaona et al [7] propose a novel bit based component combination calculation approach in the mix of face and ear. The component combination approach was acquainted and applied multimodal biometrics dependent on the ear and profile face biometrics combination, in blend with the KPCA or KFDA calculation.…”
Section: Related Workmentioning