Ciphertext image retrieval method and system under a cloud environment

A technology of image retrieval and cloud environment, which is applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve problems such as hash function and hash table optimization

Active Publication Date: 2018-12-07
CENTRAL SOUTH UNIVERSITY OF FORESTRY AND TECHNOLOGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But the scheme does not optimize the hash function and hash table

Method used

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  • Ciphertext image retrieval method and system under a cloud environment
  • Ciphertext image retrieval method and system under a cloud environment
  • Ciphertext image retrieval method and system under a cloud environment

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Experimental program
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Embodiment 1

[0098] Embodiment 1: as figure 1 , an introduction to the system model

[0099] The present invention adopts a similar model in the literature [2], such as figure 1 As shown, there are three modules: data owner, authorized user and cloud service provider.

[0100] Cloud service providers provide content-based encrypted image retrieval. The authorized user generates and submits a search request to the cloud service provider, and the cloud service provider performs a similarity comparison and returns the sorted search results to the authorized user.

[0101] The query user has the authorization of the data owner, and the query image Represent an image in the image library and extract the feature set and generate the query vector no q Indicates the query image library M q number of images. Any G′ in the feature set i Can represent an image, each G' i It is a feature vector of [feature points*64] dimension, and each query vector represents an image, which is a 1*128...

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PUM

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Abstract

The invention discloses a ciphertext image retrieval method and system under a cloud environment. Firstly, a Harris algorithm is optimized from two aspects of an adaptive threshold value and a featurepoint pre-screening, and image features are extracted. Secondly, the Harris corner eigenvector of each image is generated by SURF algorithm and sack model. Then, a locality sensitive hashing (LSH) algorithm is used to construct a searchable index of feature vectors, and the image and index are encrypted by traditional encryption schemes. Finally, a secure similarity retrieval is performed on a cloud server. The experimental result proves that by optimizing the Harris corner selection and the feature description of the SURF and the sack model, and optimizing the parameters of the local sensitive hash algorithm, the retrieval scheme proposed by the invention, compared with existing conventional encrypted retrieval scheme, shortens the feature extraction time and also effectively improves the encrypted image retrieval efficiency.

Description

technical field [0001] The invention relates to a ciphertext image retrieval method and system in a cloud environment. Background technique [0002] Text search definition: [0003] Encrypt the private image that needs to be protected and upload it to the cloud server. The encrypted image set is uploaded here. The search is based on the user's needs. The user may input an image, and then perform a corresponding search on the cloud to find the one that meets the requirements. The images fed back to the user can be multiple images, sorted by similarity, and the number of images fed back to the user (that is, the number of the most similar images) can be set. [0004] Ciphertext image retrieval means encrypting plaintext images, that is, ordinary images, especially for private images. Even if an unauthorized user obtains the image after encrypting the private image, the image will be garbled. [0005] Ciphertext image retrieval in the cloud computing environment is the key to...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/46G06K9/62
CPCG06V10/464G06F18/22G06F18/23
Inventor 秦姣华李浩向旭宇潘丽丽谭云马文涛
Owner CENTRAL SOUTH UNIVERSITY OF FORESTRY AND TECHNOLOGY
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