Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Multiple exemplar-based facial image retrieval using independent component analysis.

Jayanta Basak1, Koustav Bhattacharya, Santanu Chaudhury

  • 1IBM India Research Lab, New Delhi 110016, India.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|December 13, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Representation learning approach for understanding structured documents.

Scientific reports·2025
Same author

Silicodata: An Annotated Benchmark CXR Dataset for Silicosis Detection.

Scientific data·2025
Same author

A decentralized privacy-preserving XR system for 3D medical data visualization using hybrid biometric cryptosystem.

Scientific reports·2025
Same author

A novel abnormality annotation database for COVID-19 affected frontal lung X-rays.

PloS one·2022
Same author

Multi-task driven explainable diagnosis of COVID-19 using chest X-ray images.

Pattern recognition·2021
Same author

Block Sparse Variational Bayes Regression Using Matrix Variate Distributions With Application to SSVEP Detection.

IEEE transactions on neural networks and learning systems·2020
Same journal

Style-Aware Contrastive Test-Time Adaptation: A Dual-Cache Model for Robust Vision-Language Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Semantic Frame Interpolation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Physics-Guided Cross-Modal Decoupling with Test-Time Adaptation for Hyperspectral Image Restoration.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

This study introduces a novel content-based image retrieval system using multiple examples to find images combining features from queries. Machine learning optimizes feature combinations for specialized databases, enhancing retrieval accuracy.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Image Processing

Background:

  • Traditional content-based image retrieval (CBIR) often relies on single query images.
  • Retrieving images that represent a combination of multiple concepts is challenging.
  • Existing methods may not effectively handle complex query semantics.

Purpose of the Study:

  • To design a content-based image retrieval (CBIR) system capable of handling multiple query examples.
  • To develop a novel scheme for representing image content as a combination of features from multiple examples.
  • To leverage machine learning for optimizing feature combination strategies in CBIR.

Main Methods:

  • A new scheme for representing image content using combined features from multiple query examples.

Related Experiment Videos

  • Development of a multiple example-based retrieval engine.
  • Application of machine learning techniques to generate optimal feature combination schemes for specific image classes.
  • Experimental validation on facial image databases.

    • Main Results:

    • Demonstrated effectiveness of the proposed multiple example-based retrieval system.
    • Successful representation of image content as a combination of features from diverse examples.
    • Tailored feature combination schemes generated for specialized image databases.
    • Experimental validation confirming system performance across different databases.

    Conclusions:

    • The proposed system effectively retrieves images based on combined content from multiple examples.
    • Machine learning enables adaptive feature combination for specialized image retrieval.
    • The approach offers a flexible and powerful solution for advanced CBIR applications, particularly in domains like facial image databases.