Image retrieval techniques: a survey

  • Authors

    • Aman Dureja
    • Payal Pahwa
    2017-12-28
    https://doi.org/10.14419/ijet.v7i1.2.9231
  • CBIR, Visual Features, Distance Metric Learning (DML), Deep CNN, Hash Function.

  • Abstract

    In the recent years, the development in computer technologies and multimedia applications has led to the production of huge digital images and large image databases, and it is increasing rapidly. There are several different areas in which image retrieval plays a crucial role like Medical systems, Forensic Labs, Tourism Promotion, etc. Thus retrieval of similar images is a challenge. To tackle this rapid growth in digital repositories it is necessary to develop image retrieval systems, which can operate on large databases. There are basically three techniques, which is useful for efficient retrieval of images. With these techniques, the number of methods has been modified for the efficient image retrieval of images. In this paper, we presented the survey of different techniques that has been used starting from Image retrieval using visual features and latest by the deep learning with CNN that contains the number of layers and now becomes the best base method for retrieval of images from the large databases. In the last section, we have made the analysis between various developed techniques and showed the advantages and disadvantages of various techniques.

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  • How to Cite

    Dureja, A., & Pahwa, P. (2017). Image retrieval techniques: a survey. International Journal of Engineering & Technology, 7(1.2), 215-219. https://doi.org/10.14419/ijet.v7i1.2.9231

    Received date: 2018-01-21

    Accepted date: 2018-01-21

    Published date: 2017-12-28