3D INVARIANT ESTIMATION OF AXISYMMETRICAL OBJECTS USING FOURIER DESCRIPTORS

Three-dimensional (3D) invariants are important for 3D object recognit ion and analysis. Lin and Jungthirapanich [Pattern Recognition 23, 833 -842 (1990)] have suggested the use of contour-related 3D elliptic Fou rier invariants for object recognition. Since the contour of an object depends on the view angle, recognition of an object can be unreliable . In this research, the 3D Fourier descriptor (FD) based volume-type ( V-type) and area-type (A-type) invariants are proposed and a method to estimate these invariants for axisymmetric objects is developed. Thes e invariants have the property of being invariant with translation, ro tation and scaling. With the proposed invariants, object recognition a s well as object property analysis for mass, density and dynamics can be exercised. Experiments are conducted for a cylinder, a concentrical ly cylindrical object and a wine bottle. The results show that the pro posed V- and A-type invariants remain unchanged with respect to locati on, orientation, scaling and view direction. Further, as the number of harmonics reaches 29, percentage of error for estimating the volume a nd the area reduces to 2%, with the computation time less than 0.18 on a PC486/33.