A type of biomelric authentication is ear acoustic authentication, which uses the ear canal transfer characteristic, showing the acoustic characteristics of the ear canal. In ear acoustic authentication, biological information can be acquired from both ears. However, extant literature on an accuracy improvement method using binaural features is inadequate. In this study, we experimentally determine a feature that represents the difference between each user to perform highly accurate authentication. Feature selection was performed by changing the combination of binaural features, and it was evaluated using the ratio of between-class variance and within-class variance and the Equal Error Ratio (EER). As a result, a method that concatenates the features of both ears has the highest performance.
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