UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 8
August-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2308566


Registration ID:
523734

Page Number

f565-f572

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Title

An Efficient Content Based Image Retrieval System Using Decision Tree Classifier and Particle Swarm Optimization

Abstract

Content-Based Image Retrieval (CBIR) is a technology and methodology used in computer vision and information retrieval to retrieve images from databases based on their visual content rather than metadata or text-based descriptions. Images are indexed and retrieved in CBIR systems utilizing their intrinsic visual qualities such as color, texture, shape, and other visual characteristics. Art galleries, the fashion business, medical imaging, satellite image analysis, and other industries use CBIR. Designing effective and efficient feature extraction approaches that capture the most significant parts of the visual content while minimizing computing cost is one of the problems in CBIR. Furthermore, finding the best similarity measuring metric is critical for accurate retrieval results. In this paper we have used Decision Tree Classifier and particle swarm optimization for creating a decision tree model to classify images based on their visual qualities which is the first step in using a decision tree for content-based image retrieval (CBIR). Particle Swarm Optimization is inspired by the social behavior of birds and fish. It involves a population of particles that move through a search space to find optimal solutions. Each particle adjusts its position based on its own experience and the experiences of other particles.

Key Words

Decision Tree Classifier, Content based image retrieval, Particle Swarm Optimization, Data mining

Cite This Article

"An Efficient Content Based Image Retrieval System Using Decision Tree Classifier and Particle Swarm Optimization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.f565-f572, August-2023, Available :http://www.jetir.org/papers/JETIR2308566.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"An Efficient Content Based Image Retrieval System Using Decision Tree Classifier and Particle Swarm Optimization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppf565-f572, August-2023, Available at : http://www.jetir.org/papers/JETIR2308566.pdf

Publication Details

Published Paper ID: JETIR2308566
Registration ID: 523734
Published In: Volume 10 | Issue 8 | Year August-2023
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.35909
Page No: f565-f572
Country: Prayagraj, Uttar Pradesh, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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