A contour-oriented approach to shape analysis
A contour-oriented approach to shape analysis
International Journal of Computer Vision
A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Representation Using a Generalized Potential Field Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Corner detection via topographic analysis of vector-potential
Pattern Recognition Letters
International Journal of Computer Vision
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
An Evaluation of Face and Ear Biometrics
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
A New Ear Recognition Approach for Personal Identification
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Ear Recognition with Variant Poses Using Locally Linear Embedding
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
A Fast and Fully Automatic Ear Recognition Approach Based on 3D Local Surface Features
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
Intelligent computing for automated biometrics, criminal and forensic applications
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Image and volume segmentation by water flow
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Multi-view ear recognition based on moving least square pose interpolation
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Normalizing human ear in proportion to size and rotation
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
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
The relative potential field as a novel physics-inspired method for image analysis
WSEAS Transactions on Computers
Shaped wavelets for curvilinear structures for ear biometrics
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
On guided model-based analysis for ear biometrics
Computer Vision and Image Understanding
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
Efficient Detection and Recognition of 3D Ears
International Journal of Computer Vision
The image ray transform for structural feature detection
Pattern Recognition Letters
Automated human identification using ear imaging
Pattern Recognition
WSEAS Transactions on Computers
A review of recent advances in ear recognition
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Ear recognition based on local information fusion
Pattern Recognition Letters
Human ear recognition from face profile images
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Biometric recognition based on line shape descriptors
GREC'05 Proceedings of the 6th international conference on Graphics Recognition: ten Years Review and Future Perspectives
An efficient ear localization technique
Image and Vision Computing
Ear biometrics by force field convergence
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Using ear biometrics for personal recognition
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
On using physical analogies for feature and shape extraction in computer vision
VoCS'08 Proceedings of the 2008 international conference on Visions of Computer Science: BCS International Academic Conference
Reliable ear identification using 2-D quadrature filters
Pattern Recognition Letters
A rotation and scale invariant technique for ear detection in 3D
Pattern Recognition Letters
Multibiometric human recognition using 3D ear and face features
Pattern Recognition
ACM Computing Surveys (CSUR)
3D pure ear extraction and recognition
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Robust ear based authentication using Local Principal Independent Components
Expert Systems with Applications: An International Journal
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The overall objective in defining feature space is to reduce the dimensionality of the original pattern space, whilst maintaining discriminatory power for classification. To meet this objective in the context of ear biometrics a new force field transformation treats the image as an array of mutually attracting particles that act as the source of a Gaussian force field. Underlying the force field there is a scalar potential energy field, which in the case of an ear takes the form of a smooth surface that resembles a small mountain with a number of peaks joined by ridges. The peaks correspond to potential energy wells and to extend the analogy the ridges correspond to potential energy channels. Since the transform also turns out to be invertible, and since the surface is otherwise smooth, information theory suggests that much of the information is transferred to these features, thus confirming their efficacy. We previously described how field line feature extraction, using an algorithm similar to gradient descent, exploits the directional properties of the force field to automatically locate these channels and wells, which then form the basis of characteristic ear features. We now show how an analysis of the mechanism of this algorithmic approach leads to a closed analytical description based on the divergence of force direction, which reveals that channels and wells are really manifestations of the same phenomenon. We further show that this new operator, with its own distinct advantages, has a striking similarity to the Marr-Hildreth operator, but with the important difference that it is non-linear. As well as addressing faster implementation, invertibility, and brightness sensitivity, the technique is also validated by performing recognition on a database of ears selected from the XM2VTS face database, and by comparing the results with the more established technique of Principal Components Analysis. This confirms not only that ears do indeed appear to have potential as a biometric, but also that the new approach is well suited to their description, being robust especially in the presence of noise, and having the advantage that the ear does not need to be explicitly extracted from the background.