Biometric Authentication System using Human Ear
Namitha Santhosh, Nefla Afsal, Tia Roshan, Sandra Franco, Liya Joseph
Authentication, Biometrics, Ear, Contour Detection, Feature vectors
In this paper, a fully-automated ear-based biometric authentication system is proposed. Biometric authentication technology has become widespread, with the mainstream methods being fingerprint authentication and face recognition. However, fingerprint authentication cannot be used when hands are wet, and face recognition cannot be used when a person is wearing a mask. Like the face and fingers, the ear as a biometric contains features that enable human identification and has been the subject of research on personal authentication. The advantages of using the ear as a biometric is that undamaged ears are more or less the same until a person reaches 70 years old. YOLOv3 (You Only Look Once) is used to segment each user's image. After segmentation, noise is eliminated using Gaussian blur. Different methods are then subsequently applied to the resulting binary contour image for the purpose of feature extraction. Prominent contours associated with the folds of the ear shell are detected. The extracted features are then compared with the existing features in the database using feature matching. Once verified, the user will be granted access.
Article Details
Unique Paper ID: 160077

Publication Volume & Issue: Volume 9, Issue 12

Page(s): 1257 - 1261
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