A New Segmentation Approach for Ear Recognition
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Connected component based technique for automatic ear detection
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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
Efficient Detection and Recognition of 3D Ears
International Journal of Computer Vision
An efficient ear localization technique
Image and Vision Computing
A review of recent advances in 3D ear- and expression-invariant face biometrics
ACM Computing Surveys (CSUR)
ACM Computing Surveys (CSUR)
Entropy based Binary Particle Swarm Optimization and classification for ear detection
Engineering Applications of Artificial Intelligence
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This paper presents an efficient approach for localization of ear from an arbitrary 2-D side face image with varying background. Outer helix curves of ears moving parallel to each other are used as feature for localizing ear in an image. Using Canny edge detector edges are extracted from the whole image. These edges are segmented in convex and concave edges. From these segmented edges expected outer helix edges are determined after eliminating non-ear edges. Final outer helix edge of an ear is constructed using expected outer helix curves. Decision is made on a constructed curve whether it belongs to outer helix of ear or not. This technique is implemented on IITK, India database containing 700 samples. Accuracy of localization is more than 93%.