Applying metric space and pivot-based indexing on combined features of bio-images for fast execution of composite queries

  • Authors

    • Meenakshi Srivastava Amity University
    • S.K. Singh Amity University
    • S.Q. Abbas Ambalika Institute of Management and Technology
  • Image Retrieval, Metric Space, Protein Structures, AESA, LAESA, Pivot Indexing.
  • Content based recovery of bio images requires index structures, which can retrieve the similar image objects in time proficient way. Conventional Structure/ sequence based recovery of bio-images (for example, protein structures) experiences, tedious online similarity check from huge web based databases. The general approach of image feature representations follows vector based portrayal. In present manuscript, visual highlights of 3D protein structures and their content highlights have been implemented in isolated metric space, rather than vector space which advances the similarity recovery. At long last, the Visual highlights and Content based highlights are consolidated in one metric space, through the component results of highlight and substance metric. Results have demonstrated that pivot based ordering/ indexing on Combined Index Metric can undoubtedly execute composite content construct queries with respect to bio images in time effective way.

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    Srivastava, M., Singh, S., & Abbas, S. (2018). Applying metric space and pivot-based indexing on combined features of bio-images for fast execution of composite queries. International Journal of Engineering & Technology, 7(1), 110-114.