title: Algorithm for image retrieval based on edge gradient orientation statistical code.
abstract: 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 n-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.
authors.affiliation: School of Software, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China.
authors.forename: Jiexian
authors.initials: J
authors.lastname: Zeng
authors.affiliation: School of Software, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China.
authors.forename: Yonggang
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: School of Software, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China.
authors.forename: Weiye
authors.initials: W
authors.lastname: Li
authors.affiliation: School of Software, Nanchang Hangkong University, Nanchang, Jiangxi 330063, China.
authors.forename: Xiang
authors.identifier: 0000-0003-3750-9698
authors.initials: X
authors.lastname: Fu
mesh_terms: D000465:Algorithms; D019277:Entropy; D016247:Information Storage and Retrieval; D015233:Models, Statistical