MATEC Web Conf.
Volume 173, 20182018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|Number of page(s)||5|
|Section||Digital Signal and Image Processing|
|Published online||19 June 2018|
Image Retrieval Algorithm Based on Minimal Loss Hashing
Graphic image and multimedia lab, Chongqing University of Posts and Telecommunication, Chongqing, China
2 Graphic image and multimedia lab, Chongqing University of Posts and Telecommunication, Chongqing, China
In order to solve the inefficiency and time-consuming of traditional image retrieval algorithms, an image retrieval algorithm based on minimal loss hashing is proposed. Firstly, the original high dimensional data is reduced by principal component analysis and Laplacian Eigenmaps. Secondly, minimize dimensionality reduction and quantization coding loss function, then we could obtain the hash function by iterative optimization parameters. Finally, the original data matrix is converted into a hash coding matrix, and the sample similarity is obtained by calculating the Hamming distance between samples. The experimental results on four public datasets show that the proposed method improves the retrieval performance.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.