This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors’ approach is to search only the corners near enhanced edges and, by a z-score normalisation, to avoid the introduction of the linear combination coefficient. Combining these strategies allows a fine and stable corner selection without tuning the method. The new detector has been compared with other state-of-the-art detectors on the standard Oxford data set, achieving good results showing the validity of the approach. Analogous results have been obtained using the local detector evaluation framework on non-planar scenes by Fraundorfer and Bischof.
Bellavia, F., Tegolo, D., Valenti, C.F. (2011). Improving Harris corner selection strategy. IET COMPUTER VISION, 5, 87-96 [10.1049/iet-cvi.2009.0127].
Improving Harris corner selection strategy
BELLAVIA, Fabio;TEGOLO, Domenico;VALENTI, Cesare Fabio
2011-01-01
Abstract
This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors’ approach is to search only the corners near enhanced edges and, by a z-score normalisation, to avoid the introduction of the linear combination coefficient. Combining these strategies allows a fine and stable corner selection without tuning the method. The new detector has been compared with other state-of-the-art detectors on the standard Oxford data set, achieving good results showing the validity of the approach. Analogous results have been obtained using the local detector evaluation framework on non-planar scenes by Fraundorfer and Bischof.File | Dimensione | Formato | |
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