Content-based image retrieval using wavelets

Abstract:- This paper presents a novel approach for content-based image retrieval (CBIR) that provides the analysis of visual information using wavelet coefficients and similarity metrics. This approach has a better performance than well-known RedNew CBIR system based on image indexing and retrieval using neural networks. A principal goal of this report is precise analysis of the four families of wavelets and three techniques for computing similarity. The best Symlet transform and similarity metrics based on Euclidian distance have been adopted in a proposed system called Image Retrieval by Wavelet Coefficients IRWC. In order to test a proposed system the recall and precision metrics used for evaluating the performance of CBIR facilities have been used on base of the standard COIL-100 image collections. The obtained results show the increment of retrieval efficiency up to 92 % without additional increasing a processing time. Therefore a proposed approach may be considered as a good alternative for design of new CBIR systems. Key-Words:- Image processing, visual information retrieval, similarity metrics, wavelets 1

Authors

Institutions

Publication Details

Published
2025-02-21
DOI
https://doi.org/10.5281/zenodo.14907910
Citations
15
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Content-based image retrieval using wavelets

Leticia Flores-Pulido
15 citations
Image Retrieval and Classification Techniques
article

Content-based image retrieval using wavelets

Leticia Flores-Pulido
article en
15 citations

Abstract

Abstract:- This paper presents a novel approach for content-based image retrieval (CBIR) that provides the analysis of visual information using wavelet coefficients and similarity metrics. This approach has a better performance than well-known RedNew CBIR system based on image indexing and retrieval using neural networks. A principal goal of this report is precise analysis of the four families of wavelets and three techniques for computing similarity. The best Symlet transform and similarity metrics based on Euclidian distance have been adopted in a proposed system called Image Retrieval by Wavelet Coefficients IRWC. In order to test a proposed system the recall and precision metrics used for evaluating the performance of CBIR facilities have been used on base of the standard COIL-100 image collections. The obtained results show the increment of retrieval efficiency up to 92 % without additional increasing a processing time. Therefore a proposed approach may be considered as a good alternative for design of new CBIR systems. Key-Words:- Image processing, visual information retrieval, similarity metrics, wavelets 1

Universidad Autónoma de Tlaxcala (MX)
Openalex Percentile: Top 100%
Image Retrieval and Classification Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.