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April 29, 2026Open Access

Content Based Image Retrieval Using Texture And Color Features

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Authors

MTMahadu. A. Trimukhe

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Overview

Randomized trial explores how texture and color features improve image retrieval, suggesting enhanced accuracy.

Key Points

  • This paper aims to address the challenges of designing an effective Content Based Image Retrieval (CBIR) system.
  • Utilized texture features extracted via the Haar wavelet transform.
  • Employed color feature extraction using color moments.
  • Computed the distance between query image features and database images for similarity.
  • Demonstrated significant improvements in retrieval accuracy using multiple features compared to a single feature.
  • Highlighted the effectiveness of Haar wavelet transform and color moments in enhancing CBIR performance.

Cite This Study

Mahadu. A. Trimukhe (2026) studied this question.

synapsesocial.com/papers/69f19ff5edf4b46824806aafhttps://doi.org/10.5281/zenodo.19827795
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Novel Content-based Image Retrieval System using Fusing Color and Texture Features2022
  2. 2AI powered multi feature fusion framework for retrieving images using color, texture and shape descriptors2025 · 3 citations
  3. 3Image Retrieval based on Multi-features using Fuzzy Set2022
  4. 4A Framework for Extensive Content-Based Image Retrieval System Incorporating Relevance Feedback and Query Suggestion2024 · 11 citations
  5. 5Study and Development of Content Based Image Retrieval (CBIR) Using Multiple Features on Android Platform2025