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Most 3D object recognition methods use mean-Gaussian curvatures (HK) or shape index-curvedness (SC) values for classification. Although these two curvature descriptions classify objects into same categories, their mathematical definitions vary. In this study a comparison 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 transformation is proposed. The results show that scale and resolution invariant HK curvature values gives better recognition results compared to SC curvature values.