Cloud Space Optimization by Preventing Similar Image Insertion Using Hashing Based on Feature Point

  • Authors

    • Radhika Nambiar
    • Prithvi A
    • Priyanka A
    • Suma M Shirahatti
    • Prof. Radhakrishna Dodmane
    2018-12-13
    https://doi.org/10.14419/ijet.v7i4.39.28358
  • A-Hash, D-hash, P-hash, Feature extraction, DCT, MSER, Correlation coefficient factor etc.

  • People tend to click a lot of pictures in their phones or they download images from the internet. When these images are uploaded to cloud, there is high possibility of similar images being already present which were uploaded earlier. This leads to the wastage of space and related issues. For efficient utilization of cloud space, the proposed system provides a framework to determine duplicate images in the cloud. The duplicate images are determined using hash value as a key parameter. The hash values of the image are generated using perceptual image hashing algorithms. Since these algorithms are geometric transformation variant, the proposed system is developed based on feature extraction and image hashing. This will ensure more accuracy. The system is compared with existing algorithm based on accuracy and the results are shown.

     

     

  • References

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  • How to Cite

    Nambiar, R., A, P., A, P., M Shirahatti, S., & Radhakrishna Dodmane, P. (2018). Cloud Space Optimization by Preventing Similar Image Insertion Using Hashing Based on Feature Point. International Journal of Engineering & Technology, 7(4.39), 1042-1046. https://doi.org/10.14419/ijet.v7i4.39.28358