Title :
A transformation-invariant recursive subdivision method for shape analysis
Author :
Zhu, Qiuming ; Poh, Lay-kheng
Author_Institution :
Sch. of Eng. & Comput. Sci., Oakland Univ., Rochester, MI, USA
Abstract :
A method is presented for shape analysis by recursive subdivisions. The subdivisions are invariant with respect to translation, scaling, rotation, and intensity shifting. Eigenvectors of the second central movements are used to derive such subdivisions. A hierarchical shape description uses the invariants defined on the second central moments of the subdivisions. The approach emphasizes the local feature for recognizing object shapes as similar
Keywords :
pattern recognition; picture processing; eigenvectors; hierarchical shape description; intensity shifting; pattern recognition; picture processing; rotation; scaling; shape analysis; transformation-invariant recursive subdivision method; translation; Computer science; Covariance matrix; Digital images; Eigenvalues and eigenfunctions; Equations; Image analysis; Image converters; Probability distribution; Shape; Symmetric matrices;
Conference_Titel :
Pattern Recognition, 1988., 9th International Conference on
Conference_Location :
Rome
Print_ISBN :
0-8186-0878-1
DOI :
10.1109/ICPR.1988.28373
