SCIENCE@home

Ontology-based Secure Retrieval of Semantically Significant Visual Contents

Khan Muhammad,I. Mehmood,Mi Young Lee,S. Ji,S. Baik

Published 2015 in arXiv.org

ABSTRACT

Image classification is an enthusiastic research field where large amount of image data is classified into various classes based on their visual contents. Researchers have presented various low-level features-based techniques for classifying images into different categories. However, efficient and effective classification and retrieval is still a challenging problem due to complex nature of visual contents. In addition, the traditional information retrieval techniques are vulnerable to security risks, making it easy for attackers to retrieve personal visual contents such as patients records and law enforcement agencies databases. Therefore, we propose a novel ontology-based framework using image steganography for secure image classification and information retrieval. The proposed framework uses domain-specific ontology for mapping the low-level image features to high-level concepts of ontologies which consequently results in efficient classification. Furthermore, the proposed method utilizes image steganography for hiding the image semantics as a secret message inside them, making the information retrieval process secure from third parties. The proposed framework minimizes the computational complexity of traditional techniques, increasing its suitability for secure and real-time visual contents retrieval from personalized image databases. Experimental results confirm the efficiency, effectiveness, and security of the proposed framework as compared with other state-of-the-art systems.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    arXiv.org

  • Publication date

    2015-10-08

  • Fields of study

    Computer Science

  • Identifiers
    arXiv 1510.02177
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-21 of 21 references · Page 1 of 1

CITED BY

Showing 1-15 of 15 citing papers · Page 1 of 1