Abstract
A new template matching scheme for the detection of objects on the basis of orientations is proposed. The matching scheme is based on correlations in the domain \(\mathbb{R}^2 \rtimes S^1\) of complex valued invertible orientation scores. In invertible orientation scores, a comprehensive overview of how an image is decomposed into local orientations is obtained. The presented approach allows for the efficient detection of orientation patterns in an intuitive and direct way. Furthermore, an energy minimization approach is proposed for the construction of suitable templates. The method is applied to optic nerve head detection in retinal images and extensive testing is done using images from both public and private databases. The method correctly identifies the optic nerve head in 99.7% of 1737 images.
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