Study of Different Features and Classifiers for Image Retrieval

  • Authors

    • Arpana Mahajan
    • Sanjay Chaudhary
    2018-11-27
    https://doi.org/10.14419/ijet.v7i4.19.22015
  • Automatic image retrieval, Low Level features, Classification, Distances.

  • Abstract

    With the advent of multimedia and imaging technology, lots of   images sharing and uploading over the internet have been increased. It instigated development of potential image retrieval system to satisfy the requirement of mankind. The content-based image retrieval (CBIR) system retrieves the desired image by low level features similar to color, shape and texture which are not enough to explain the user’s high level perception for images. Therefore reducing this semantic gap problem of image retrieval is challenging task. Some of the concepts in image retrieval are keywords, conditions or text. Conditions are used by human to explain their information need and it also used by system as a way to stand for images. Here in this paper different types of features their advantage and disadvantages are described.

     

     

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  • How to Cite

    Mahajan, A., & Chaudhary, S. (2018). Study of Different Features and Classifiers for Image Retrieval. International Journal of Engineering & Technology, 7(4.19), 58-62. https://doi.org/10.14419/ijet.v7i4.19.22015

    Received date: 2018-11-28

    Accepted date: 2018-11-28

    Published date: 2018-11-27