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A survey of image data indexing techniques

  • Saurabh Sharma
  • Vishal GuptaEmail author
  • Mamta Juneja
Article
  • 199 Downloads

Abstract

The Index is a data structure which stores data in a suitably abstracted and compressed form to facilitate rapid processing by an application. Multidimensional databases may have a lot of redundant data also. The indexed data, therefore need to be aggregated to decrease the size of the index which further eliminates unnecessary comparisons. Feature-based indexing is found to be quite useful to speed up retrieval, and much has been proposed in this regard in the current era. Hence, there is growing research efforts for developing new indexing techniques for data analysis. In this article, we propose a comprehensive survey of indexing techniques with application and evaluation framework. First, we present a review of articles by categorizing into a hash and non-hash based indexing techniques. A total of 45 techniques has been examined. We discuss advantages and disadvantages of each method that are listed in a tabular form. Then we study evaluation results of hash based indexing techniques on different image datasets followed by evaluation campaigns in multimedia retrieval. In this paper, in all 36 datasets and three evaluation campaigns have been reviewed. The primary aim of this study is to apprise the reader of the significance of different techniques, the dataset used and their respective pros and cons.

Keywords

Image retrieval Hashing Metric Indexing Nearest-neighbor search 

Notes

Acknowledgements

The authors thank the reviewers for their helpful comments. First author would like to thank Ministry of Electronics and IT, Government of INDIA, for providing fellowship under Grant number: PhD-MLA/4(61)/2015-16 (Visvesvaraya PhD Scheme for Electronics and IT) to pursue his Ph.D. work.

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© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.University Institute of Engineering and TechnologyPanjab UniversityChandigarhIndia

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