Online 3D Ear Recognition by Combining Global and Local Features.
Where this comes from
- Record sourced from PubMed, PMID 27935955.
- Also identified by DOI 10.1371/journal.pone.0166204 and PMC identifier 5147820.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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%.
Medical subject headings
- Biometric Identification
- Ear
- Image Processing, Computer-Assisted
- Imaging, Three-Dimensional
- Machine Learning