Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Parallel algorithms for extracting ridges and ravines
PAS '95 Proceedings of the First Aizu International Symposium on Parallel Algorithms/Architecture Synthesis
Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Ear Detection from Side Face Range Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
Toward unconstrained ear recognition from two-dimensional images
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
Automated human identification using ear imaging
Pattern Recognition
Reliable ear identification using 2-D quadrature filters
Pattern Recognition Letters
ACM Computing Surveys (CSUR)
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In this paper, we present a novel system for ear identification from profile images of the face. The system has two steps. In the first step, the ear is automatically detected from the profile image of the face. In the second step, the ear image is transformed to a force field, then feature points are extracted and the best match is found from a database. We propose a method based on differential geometry to extract ear feature points. We use a transformation of the ear image to make it suitable for extracting the feature points using differential geometry. During recognition, the feature points obtained from a query image are aligned and compared with those in the database using Hausdorff distance. The experimental results show that our method is effective.