First to enhance the input image databases, pre-processing of images is initially made. Then only the features from the ear modalities are extracted effectively. Then the ear features are extracted using shape based Active Appearance Model (AAM). Then using chaff points and these two extracted feature points, a grouped feature vector point is obtained. After getting the grouped feature vector points, the secret key points are added with the grouped feature vector points to make the fuzzy vault. Finally, test person’s grouped vector is compared with the fuzzy vault data base to recognize correct person.
Face Image and Ear Image.
Classified whether it is matched ear or not matched ear for the given input face Image.
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[1]Jatit.org, 2020. [Online]. Available: http://www.jatit.org/volumes/Vol59No2/9Vol59No2.pdf. [Accessed: 28- Sep- 2020]. [2]G. Amirthalingam and G. Radhamani, "Multimodal Biometric Cryptosystem for Face and Ear Recognition Based on Fuzzy Vault", Research Journal of Applied Sciences, Engineering and Technology, vol. 7, no. 20, pp. 4211-4219, 2014. Available: 10.19026/rjaset.7.791. [3]"LAS VEGAS SANDS CORP., a Nevada corporation, Plaintiff, v. UKNOWN REGISTRANTS OF Defendants.", Gaming Law Review and Economics, vol. 20, no. 10, pp. 859-868, 2016. Available: 10.1089/glre.2016.201011.