International Journal on Science and Technology

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Enhanced Content Based Image Retrieval Using Integrated Color and Texture Features

Author(s) Ranjeet Kumar, Dr. Narasimha Murthy M S
Country India
Abstract Content-Based Image Retrieval (CBIR) has emerged as a crucial technique for collecting images from large databases based on their visual content, such as color, texture and shape. This paper introduces an enhanced CBIR system that combines color and texture features to enhance retrieval accuracy and performance. However, challenges related to dimensionality reduction, illumination variations, and feature selection remain, offering directions for future research.
Keywords Content-Based Image Retrieval (CBIR), Color Features, Texture Features, Color Histogram, Gray-Level Co-occurrence Matrix (GLCM), Local Binary Patterns (LBP), Gabor Filters, Feature Fusion, Similarity Measure, Euclidean Distance, Cosine Similarity, Image Retrieval, Dimensionality Reduction, Image Database, Visual Content, Image Matching.
Field Engineering
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-01-13
Cite This Enhanced Content Based Image Retrieval Using Integrated Color and Texture Features - Ranjeet Kumar, Dr. Narasimha Murthy M S - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.1418
DOI https://doi.org/10.71097/IJSAT.v16.i1.1418
Short DOI https://doi.org/g82pb4
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