A Comprehensive Analysis of Feature Extraction and Retrieval Techniques used in Content-Based Image Retrieval Systems

In this paper, the literature review about various feature extraction methods adopted for extracting feature of query image and database images has been discussed. There are main two approaches to implement content based retrieval system. First is the conventional machine learning methods another is deep learning convolution neural network architectures. Efforts are made for detailed survey of both the machine learning and deep learning approaches for the purpose of extraction of most important salient features of images directly affecting the retrieval performance for classifying the images in particular category and finally retrieving most relevant top images.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-21
DOI
https://doi.org/10.52783/jisem.v10i38s.7158
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A Comprehensive Analysis of Feature Extraction and Retrieval Techniques used in Content-Based Image Retrieval Systems

Nisha Gupta
Journal of Information Systems Engineering & Management
Image Retrieval and Classification Techniques
article

A Comprehensive Analysis of Feature Extraction and Retrieval Techniques used in Content-Based Image Retrieval Systems

Nisha Gupta
article en

Abstract

In this paper, the literature review about various feature extraction methods adopted for extracting feature of query image and database images has been discussed. There are main two approaches to implement content based retrieval system. First is the conventional machine learning methods another is deep learning convolution neural network architectures. Efforts are made for detailed survey of both the machine learning and deep learning approaches for the purpose of extraction of most important salient features of images directly affecting the retrieval performance for classifying the images in particular category and finally retrieving most relevant top images.

Journal of Information Systems Engineering & ManagementVol. 10(38s)
Openalex Percentile: Top 93%
Image Retrieval and Classification Techniques
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