2134/24204 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.