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Dr. Shady Yehia AbdElazim Elmashed :: Publications:

Title:
A More Robust Feature Correspondence for More Accurate Image Recognition
Authors: Shady Y. El-Mashad and Amin Shoukry
Year: 2014
Keywords: Features Matching; Local Features; Global Features; Topological Relations; Graph Matching; Quadratic Assignment Problem.
Journal: Canadian Conference on Computer and Robot Vision
Volume: 11
Issue: Not Available
Pages: 181-188
Publisher: IEEE
Local/International: International
Paper Link:
Full paper Shady Yehia AbdElazim Elmashed _A More Robust Feature Correspondence for More Accurate Image Recognition.pdf
Abstract:

In this paper, a novel algorithm for finding the optimal correspondence between two sets of image features has been introduced. The proposed algorithm pays attention not only to the similarity between features but also to the spatial layout of every matched feature and its neighbors. Unlike related methods that use geometrical relations between the neighboring features, the proposed method employes topology that survives against different types of deformations like scaling and rotation; resulting in more robust matching. The features are expressed as an undirected graph where every node represents a local feature and every edge represents adjacency between them. The topology of the resulting graph can be considered as a robust global feature of the represented object. The matching process is modeled as a graph matching problem; which in turn is formulated as a variation of the quadratic assignment problem. In this variation, a number of parameters are used to control the significance of global vs. local features to tune the performance and customize the model. The experimental results show a significant improvement in the number of correct matches using the proposed method compared to different methods.

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