The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 53-322
Full Name: Mary Praveena
Position: Assistant Professor
Age: ON
Sex: Female
Address: 12/17 kk nagar,ganapathy
Country: INDIA
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E-mail address: praveena_infant@yahoo.co.in
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Title of the Paper: Multimodal Biometric Image Fusion System
Authors as they appear in the Paper: S.Mary Praveena , Dr.Ila Vennila
Email addresses of all the authors: praveena_infant@yahoo.co.in, iven@eee.psgtech.ac.in
Number of paper pages: 10
Abstract: Abstract - In the real world applications, unimodal biometric systems often face limitations because of sensitivity to noise, intra class invariability, data quality, and other factors. Improving the performance of individual matchers in the aforementioned situation may not be effective. Multi biometric systems are used to overcome this problem by providing multiple pieces of evidence of the same identity. This system provides effective fusion scheme that combines information presented by the multiple domain experts based on the Rank level fusion integration method, thereby increasing the efficiency of the system which is not possible by the unimodal biometric system. The proposed multimodal biometric system has a number of unique qualities, starting from utilizing principal component analysis and fisher's linear discriminate methods for individual matchers authentication and the novel rank level fusion method is used in order to consolidate the results obtained fr!
om different biometric matchers. The ranks of the individual matchers are combined using highest rank, borda count, and logistic regression method. From the results it can be concluded that the overall performances of the multi biometric systems are improved even in the presence of poor quality of data.
Keywords: - Singular value decomposition (SVD), Pattern recognition, Multi biometric system, Rank level fusion, Principal Component Analysis (PCA),Biometrics.
EXTENSION of the file: .doc
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