NDLI: Ear recognition based on weighted wavelet transform and DCT

Content Provider	IEEE Xplore Digital Library
Author	Tian Ying Zhang Debin Zhang Baihuan
Copyright Year	2014
Description	Author affiliation: Coll. of Software, Univ. of Sci. & Technol. LiaoNing, Anshan, China (Tian Ying; Zhang Debin; Zhang Baihuan)
Abstract	Feature extraction is the key to improve the ear recognition. Firstly, we conduct two dimensional discrete wavelet transform on the human ear images, and then we implement block discrete cosine transform on the low frequency components of wavelet transform and weighted high-frequency components in order to extract DCT coefficients of the image and construct the feature vectors. Finally, we use the nearest neighbor classifier combined with weighted distance for classification and recognition.. The experimental results show that the new method has a higher recognition rate compared with the method in which only the low frequency components of wavelet transform are used.
Starting Page	4410
Ending Page	4414
File Size	916515
Page Count	5
File Format	PDF
ISBN	9781479937073
e-ISBN	9781479937080
DOI	10.1109/CCDC.2014.6852957
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time-frequency analysis block discrete cosine transform Ear two-dimensional discrete wavelet transform nearest neighbor classifier Feature extraction ear recognition Discrete wavelet transforms Discrete cosine transforms weighted distance
Content Type	Text
Resource Type	Article

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