This paper suggests the use of symmetric patterns and their corresponding symmetry filters for pattern recognition in computer vision tasks involving multiple views and scales. Symmetry filters enable efficient computation of certain structure features as represented by the generalized structure tensor (GST). The properties of the complex moments to changes in scale and multiple views including in-depth rotation of the patterns and the presence of noise is investigated. Images of symmetric patterns captured using a low resolution low-cost CMOS camera, such as a phone camera or a web-cam, from as far as three meters are precisely localized and their spatial orientation is determined from the argument of the second order complex moment I 20 without further computation. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Teferi, D., & Bigun, J. (2009). Multi-view and multi-scale recognition of symmetric patterns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5575 LNCS, pp. 657–666). https://doi.org/10.1007/978-3-642-02230-2_67
Mendeley helps you to discover research relevant for your work.