title: Online 3D Ear Recognition by Combining Global and Local Features.
abstract: The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.
authors.affiliation: Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China.
authors.forename: Yahui
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Computer and Information Science, University of Macau, Macau.
authors.forename: Bob
authors.initials: B
authors.lastname: Zhang
authors.affiliation: Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China.
authors.forename: Guangming
authors.initials: G
authors.lastname: Lu
authors.affiliation: Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China.
authors.forename: David
authors.initials: D
authors.lastname: Zhang
mesh_terms: D056667:Biometric Identification / Q000295:instrumentation / Q000379:methods*; D066264:Datasets as Topic; D004423:Ear / Q000033:anatomy & histology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data*; D021621:Imaging, Three-Dimensional / Q000706:statistics & numerical data*; D007834:Lasers; D000069550:Machine Learning