Encrypted Image Retrieval System based on Features Analysis

Author:

GAATA Methaq Talib,Fouad Hantoosh Fadya

Abstract

Abstract – Content-based search provides an important tool for users to consume the ever-growing digital media repositories. However, since communication between digital products takes place in a public network, the necessity of security for digital images becomes vital. Hence, the design of secure content-based image retrieval system is becoming an increasingly demanding task as never before. This paper, presents a mechanism that addresses the secure CBIR as a novel improvement and application for the image retrieval. The proposed system consists of six phases briefly described as follows: first, feature extraction phase, which produces the low-level quantitative description of the image (color and texture) that allows the computation of similarity measures, the definition of the ordering of the images, and the indexing of the search processes. Second, indexing for search process phase, hash table and bloom filter were employed for classification. Third, feature encryption phase, where content protection is performed using a method developed by us (including Chaotic Logistic Map). Fourth,  image encryption phase, as security mechanism for CBIR, we combine two research fields in computer science, CBIR and image cryptography, which grow up to meet the trends of security and speed in current computer sciences, chaos and stream cipher systems were applied as an image encryption system. Fifth, the retrieval phase, which provides a subset of images answering the query based on the similarity between images computed over the feature vector extracted from each image. Finally, Relevance feedback phase, a technique that attempts to capture the user’s needs through iterative feedback. Although the system proved its efficiency in search performance (with 88% of average precision), security strength, and computational complexity, it does not mean the optimal system is designed, since some weakness points still can be found that are suggested to be improved as a future work.

Publisher

Al-Mustansiriyah Journal of Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Content based Image Retrieval with Rocchio Algorithm for Relevance Feedback Using 2D Image Feature Representation;Proceedings of the 2019 2nd International Conference on Machine Learning and Machine Intelligence;2019-09-18

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3