Research on Related Technology of Content-Based Image Retrieval

Yu Bing Dong; Ming Jing Li; Bai Chuan Li

doi:10.4028/www.scientific.net/AMM.448-453.3616

Paper Titles

Personalized Layer Retrieve for M-Learning Resources on Users Interest
p.3596

Research of Dynamic Target Tracking Algorithm
p.3601

Application of BP Neural Network Based on Immune Particle Swarm Optimization for Fault Diagnosis of Power Transformer
p.3605

An Improved Delay-Dependent Stability Criterion for Power System with Double Time Delays
p.3610

Research and Development of Non Multi-Scale to Pixel-Level Image Fusion
p.3621

Research and Development of Multi-Scale to Pixel-Level Image Fusion
p.3625

Research and Design of Technology Readiness Levels Evaluating System for Digital Instrumentation and Control System
p.3629

Classifications of Generalized Linear Control Systems
p.3635

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 448-453Research on Related Technology of Content-Based...

Research on Related Technology of Content-Based Image Retrieval

Abstract:

Content-Based Image Retrieval (CBIR) system existed a gap between high-level concepts and low-level features. As an effective solution, the Relevance Feedback (RF) technique has been used on many CBIR systems to improve the retrieval precision. In order to further improve convergence speed and retrieval accuracy, a novel relevance feedback method was proposed. According to feedback from user, image feature was weighted and adjusted in the novel method.

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Periodical:

Applied Mechanics and Materials (Volumes 448-453)

Pages:

3616-3620

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.448-453.3616

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Online since:

October 2013

Authors:

Yu Bing Dong, Ming Jing Li, Bai Chuan Li

Keywords:

Feature Extraction, Image Database, Image Retrieval, Relevance Feedback

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References

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