Ear Recognition Based on Point Feature

Ying Tian; De Bin  Zhang

doi:10.4028/www.scientific.net/AMM.380-384.3840

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384Ear Recognition Based on Point Feature

Ear Recognition Based on Point Feature

Abstract:

In order to improve recognition rate of human ear, a method based on point feature of image for ear recognition is proposed in this paper. Firstly force field transformation theory is applied to human ear image two times in our method. It can extract the structural feature points and contour feature points of ear respectively and compose feature point set. Then feature points described by the scale invariant feature transformation descriptor. At last nearest neighbor classifier is employed for ear recognition. Feature points extracted from ear image using force field transformation are stable, reliable and discriminative, and they are insensitive to variations in image resolution. Constructing descriptor can resolve the problems caused by lower recognition owing to illumination change, scaling transformation, rotation and minute alteration caused by pose transformation. The experimental results show that the proposed algorithm not only can effectively improve ear recognition rate but also has quite good robustness.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

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3840-3845

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.3840

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Online since:

August 2013

Authors:

Ying Tian, De Bin Zhang

Keywords:

Ear Recognition, Feature Descriptor, Feature Points Matching, Force Field Transformation

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