Privacy Preserving for Annular Distribution Density Structure Descriptor in CBIR Using Bit-plane Randomization Encryption

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 703)

Abstract

With the rapid increase in multimedia services and Internet users over the network, it is crucial to have effective and accurate retrieval while preserving data confidentiality. We propose a simple and effective content-based image retrieval algorithm using annular distribution density structure descriptor (ADDSD) to retrieve the relevant images using encrypted features to preserve the privacy of image content. It exploits the HSV color space of image to generate quantized image. The structure element is obtained using same or similar edge orientation in uniform HSV color space. The structure element is detected using the grid and based on the quantized structure image so formed. Finally, annular histogram is generated from the quantized structure image which is encrypted by bit-plane randomization technique. Experimental analysis illustrates that the proposed method retrieves the relevant images effectively and efficiently without revealing image content information.

Keywords

HSV Feature extraction Quantization Edge orientation Bit-plane randomization Annular histogram CBIR Encryption 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology (Indian School of Mines)DhanbadIndia

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