کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533379 870109 2012 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Physiological and behavioral lip biometrics: A comprehensive study of their discriminative power
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Physiological and behavioral lip biometrics: A comprehensive study of their discriminative power
چکیده انگلیسی

Compared with other traditional biometric features such as face, fingerprint, or handwriting, lip biometric features contain both physiological and behavioral information. Physiologically, different people have different lips. On the other hand, people can usually be differentiated by their talking style. Current research on lip biometrics generally does not distinguish between the two kinds of information during feature extraction and classification and the interesting question of whether the physiological or the behavioral lip features are more discriminative has not been comprehensively studied. In this paper, different physiological and behavioral lip features are studied with respect to their discriminative power in speaker identification and verification. Our experimental results have shown that both the static lip texture feature and the dynamic shape deformation feature can achieve high identification accuracy (above 90%) and low verification error rate (below 5%). In addition, the lip rotation and centroid deformations, which are related to the speaker's talking mannerism, are found to be useful for speaker identification and verification. In contrast to previous studies, our results show that behavioral lip features are more discriminative in speaker identification and verification compared to physiological features.


► Study the discriminative power of physiological and behavioral lip biometrics.
► Behavioral lip features achieve higher accuracy than physiological lip features.
► Features related to talking style are useful for speaker identification.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 45, Issue 9, September 2012, Pages 3328–3335
نویسندگان
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