Title :
3D Gray Level Moment Invariants: A Novel Shape Representation
Author :
Guo, Kehua ; Li, Min
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
Abstract :
3D moment invariants are traditionally based on region characteristics and the location of every pixel point, this will cause high calculation cost. In this paper, a novel shape representation named 3D gray level moment invariants is constructed. Some properties of the new representation including the independence of the translation, scaling and rotation transforms are proved. Experiments indicate an encouraging high recognition rates without reducing the recognition performance compared with traditional methods.
Keywords :
image representation; transforms; 3D moment invariant; 3Dshape representation; Application software; Computer vision; Costs; Image reconstruction; Image segmentation; Information science; Noise shaping; Object recognition; Shape; Working environment noise;
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
DOI :
10.1109/CCPR.2009.5344066