6533b831fe1ef96bd129908c

RESEARCH PRODUCT

Improving Harris corner selection strategy

Cesare ValentiFabio BellaviaDomenico Tegolo

subject

Settore INF/01 - Informaticabusiness.industryAutocorrelationDetectorCorner detectionGeometryScale invarianceEdge detectionAutocorrelation matrixComputer Vision and Pattern RecognitionArtificial intelligenceInvariant (mathematics)Linear combinationbusinessAlgorithmSoftwareMathematicsHarris corner detector

description

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.

10.1049/iet-cvi.2009.0127http://hdl.handle.net/10447/103475