Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37662
Title: Object recognition by combining viewpoint invariant Fourier descriptor and convex hull
Authors: Yu, MP
Lo, KC
Keywords: Computational geometry
Image classification
Image segmentation
Object recognition
Issue Date: 2001
Source: Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2001, 02 May 2001-04 May 2001, Hong Kong, p. 401-404 How to cite?
Abstract: It is observed that the shape recognition process that uses global information would fail when dealing with occlusion. In this paper, an algorithm that combines the methods of viewpoint invariant Fourier descriptor and convex hull is presented for recognizing 3D planar objects by their contours. Invariants are calculated from a set of local segments extracted from the convex hull of a shape. Under such approach, an object is represented by sets of invariant points instead of a single point in a 2D parameter space of I1 and I2. The method is efficient and yields a high recognition rate in recognizing partially occluded objects. Classification can be carried out correctly even when the convex hull of the object has changed as a result of occlusion
URI: http://hdl.handle.net/10397/37662
ISBN: 962-85766-2-3
DOI: 10.1109/ISIMP.2001.925418
Appears in Collections:Conference Paper

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