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Recent years have witnessed researchers paying enormous attention to design efficient multi-modal biometric systems because of their ability to withstand spoof attacks. Single biometric sometimes fails to extract adequate information for verifying the identity of a person [7]. On the other hand, by combining multiple modalities, enhanced performance(More)
This paper proposed the use of multi-instance feature level fusion as a means to improve the performance of Finger Knuckle Print (FKP) verification. A log-Gabor filter has been used to extract the image local orientation information, and represent the FKP features. Experiments are performed using the FKP database, which consists of 7,920 images. Results(More)
There is increased global concern to implement accurate person verification in various facets of social and professional life. These include banking, travel and secure access to social security services and defense installations. While biometrics have been deployed with reasonable success with modalities that include face, finger print, etc., the importance(More)
This paper proposes a new hybrid approach to verification aspect of a multibiometric system. This also gives a comparative analysis with traditional approaches such as multialgorithmic and multimodal versions of the same. For evaluating the performance we have considered different level of fusion with different fusion strategies for all the approaches, we(More)
In this paper, an algorithm based on the frequency domain feature extraction method is discussed for the detection of currency. This method efficiently utilizes the local spatial features in a currency image to recognize it. The entire system is pre-processed for the optimal and efficient implementation of two dimensional discrete wavelet transform (2D DWT)(More)