Optimization and integration of electronic identity authentication using a biometric indicator and RFID

In this article, individual's biometric index, radio frequency identification (RFID), and image processing are brought together in order to offer a new model of identity authentication. The suggested system has been designed in two phases: producing identity authentication card and identity confirmation. The individual's biometric image are put on a contact-less card equipped with an RFID tag and for each identity authentication, the data on the card are compared with the online biometric image. If the individual's identity is authenticated, then there will be no need for him/her to punch in the personal information since his/her information will be retrieved from the database through their electronic personal code (EPLC). This article has made use of the HMAX model which works hierarchically based on human's and some animals' visual system for extracting the features of images. Template matching has been done on the features of image taking a threshold of 0.9. To test the mentioned model, FVC2008 standard dataset containing 800 fingerprint images (8 images for 100 people) was employed. The experiments indicate that not only does the above-mentioned model show invariance to picture rotation and its scale but it also proves to be 98 percent responsive on the given dataset. The experimented pictures were also fed into the PCA model. The experiments show that the PCA has a lower identification coefficient than the HAMX model (70 percent) and it responds favorably only under controlled circumstances.