Author:
Shin Jungpil, ,Liao Hsien-Chou,
Abstract
In this paper a new interactive map search system is presented using shape context and bipartite graph matching. Shape context is used for measuring shape similarity and the recovering of point correspondences. After the above information is generated from the shape context bipartite graph matching is used to obtain the optimal correspondence between two shapes. Hierarchical description is also used to increase the recognition rate. Shape context is a method to treat shapes as a set of points and generate the histogram of the distribution of points. Wavelet analysis is used in hierarchical description. In order to shorten the calculation time, piecewise linear approximation is implemented as the feature extraction method. The systemlists the sixmost similar shapes to hand-written input shapes from the reference shapes, i.e., Japan’s 47 prefectures. Comparison results of linear matching, Dynamic Programming (DP) matching and shape context with bipartite graph matching indicate that the 1st place recognition rates are 82%, 84.52% and 92.45%, respectively. The evaluation result of hierarchical description shows that hierarchical approximation can improve the recognition rate from 92.45 to 94.97% using the deepest-4 depth. These results show that the proposed method is effective on fulfilling the interactive map search system.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
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