D. J. Buehrer1, C. S. Lu1 and C. C. Chang This email address is being protected from spambots. You need JavaScript enabled to view it.1

1Department of Computer Science and Information Engineering, National Chung Cheng University, Chaiyi, Taiwan 621, R. O. C. 


Received: May 26, 2000
Accepted: June 19, 2000
Publication Date: June 19, 2000

Download Citation: ||https://doi.org/10.6180/jase.2000.3.1.06  


An efficient shape recognition scheme based on three new ideas is presented. First, a new method is presented for estimating real-valued boundary points from the integer-valued coordinates and the grey-level values of binary images. Secondly, we can quickly determine all of the feature points with this representation by using an angle calculation formula and the separating technique which are also proposed in this paper. Then, each shape is represented by an array of pairs, where each pair contains the coordinate of a feature point and its distance from the centroid. Thirdly, in the matching process, we also propose a new split-merge technique to assist in the shape matching. The effectiveness of the shape recognition scheme is clearly proven by the good recognition rates of our experiments.

Keywords: Subpixel accuracy, real-valued coordinate representation of boundaries, feature point, shape representation, shape matching, split-merge, scaling factor, skewing


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