A new contour data compression method using Fourier descriptor

Abstract

The 3D progressive compression has received great interest in recent years, mainly due to the need for transmitting a large model over the network. This paper proposes a new compression method using Fourier descriptors for the contour shapes. Upon acquisition of the set of planar contours, a vertex list is obtained. The vertex coordinate (x, y) on the plane, is considered as a complex value (x + jy), which is transformed to the frequencies by using the Fourier descriptor. The priority filter based on the magnitude of frequencies determines the significance of the frequency components. Instead of using all frequencies, the most significant frequencies are selectively used to reconstruct the contour by the inverse Fourier transform. As a result, data size in the frequency domain is considerably reduced. Three application examples are demonstrated to show the effectiveness of the proposed method.

OP5 - A 3D-Fourier-Descriptor Approach to Compress and Classify 3D Imaging Data

“…Fourier Descriptors are introduced in [2], to provide a compact representation for 2-dimensional shapes. In [3], Kim adopted this method to a lossy compression scheme for 3D-digitized engineering components. The key aspect of this method is to represent a point cloud by a series of periodic base functions.…”