Comparison of HK and SC Curvature Descriptions in a Scale-Space for the Purpose of 3D Object Recognition

Date

2009-01-01

Author

Akagündüz, Erdem
Ulusoy, İlkay

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Most 3D object recognition methods use mean-Gaussian curvatures (HK) [2] or shape index-curvedness (SC) [3] values for classification. Although these two curvature descriptions classify objects into same categories, their mathematical definitions vary. In this study a comparion between the two curvature description is carried out for the purpose of 3D object recognition. Since unlike S; H, K and C values are not invariant of scale and resolution, a method to set them fully invariant to any transforation is proposed. The results show that scale and resolution invariant HK curvatire values gives better recognition results compared to SC curvature values.

URI

https://hdl.handle.net/11511/94121

DOI

https://doi.org/10.1109/siu.2009.5136551

Conference Name

IEEE 17th Signal Processing and Communications Applications Conference

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

E. Akagündüz and İ. Ulusoy, “Comparison of HK and SC Curvature Descriptions in a Scale-Space for the Purpose of 3D Object Recognition,” presented at the IEEE 17th Signal Processing and Communications Applications Conference, Antalya, Türkiye, 2009, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/94121.