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Jiachen Yang
Jiachen
Yang
Bin Jiang
Bin
Jiang
Baihua Li
Baihua
Li
Kun Tian
Kun
Tian
Zhihan Lv
Zhihan
Lv
A fast image retrieval method designed for network big data
Loughborough University
2017
Big data
Image retrieval
Feature ranking
Distance learning
Information and Computing Sciences not elsewhere classified
2017-02-23 15:11:30
Journal contribution
https://repository.lboro.ac.uk/articles/journal_contribution/A_fast_image_retrieval_method_designed_for_network_big_data/9402029
In the field of big data applications, image information is widely used. The value density of information utilization in big data is very low, and how to extract useful
information quickly is very important. So we should transform the unstructured image data source into a form that can be analyzed. In this paper, we proposed a fast image retrieval method which designed for big data. First of all, the feature extraction method is necessary and the feature vectors can be
obtained for every image. Then, it is the most important step for us to encode the image feature vectors and make them into
database, which can optimize the feature structure. Finally, the corresponding similarity matching is used to determined the
retrieval results. There are three main contributions for image retrieval in this paper. New feature extraction method, reasonable elements ranking and appropriate distance metric can improve the algorithm performance. Experiments show that our method
has a great improvement in the effective performance of feature extraction and can also get better search matching results.