A modified Hough scheme for general circle location
Pattern Recognition Letters
Comparative study of Hough transform methods for circle finding
Image and Vision Computing - Special issue: 5th Alvey vision meeting
DigiDu¨rer—a digital engraving system
The Visual Computer: International Journal of Computer Graphics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale Morphological Segmentations Based on Watershed, Flooding, and Eikonal PDE
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Empirical Evaluation of Advanced Ear Biometrics
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Computer Graphics Using OpenGL (3rd Edition)
Computer Graphics Using OpenGL (3rd Edition)
Computer Vision and Image Understanding
Fast and Fully Automatic Ear Detection Using Cascaded AdaBoost
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
On shape-mediated enrolment in ear biometrics
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Retinal vessel extraction with the image ray transform
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
On Using Physical Analogies for Feature and Shape Extraction in Computer Vision
The Computer Journal
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
IEEE Transactions on Image Processing
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The use of analogies to physical phenomena is an exciting paradigm in computer vision that allows unorthodox approaches to feature extraction, creating new techniques with unique properties. A technique known as the ''image ray transform'' has been developed based upon an analogy to the propagation of light as rays. The transform analogises an image to a set of glass blocks with refractive index linked to pixel properties and then casts a large number of rays through the image. The course of these rays is accumulated into an output image. The technique can successfully extract tubular and circular features and we show successful circle detection, ear biometrics and retinal vessel extraction. The transform has also been extended through the use of multiple rays arranged as a beam to increase robustness to noise, and we show quantitative results for fully automatic ear recognition, achieving 95.2% rank one recognition across 63 subjects.