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The Scientific World Journal
Volume 2014, Article ID 705763, 11 pages
Research Article

Algorithm for Image Retrieval Based on Edge Gradient Orientation Statistical Code

School of Software, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China

Received 5 December 2013; Accepted 25 March 2014; Published 30 April 2014

Academic Editors: F. Yu and G. Yue

Copyright © 2014 Jiexian Zeng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC) by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the -direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.