research-article

Research on a Scale-Based Feature Image Retrieval Algorithm

Authors:

EITCE '23: Proceedings of the 2023 7th International Conference on Electronic Information Technology and Computer Engineering

Pages 414 - 418

https://doi.org/10.1145/3650400.3650467

Published: 17 April 2024 Publication History

Get Access

Abstract

With the continued evolution of information retrieval technology, the necessity for prompt and precise image information depiction has become paramount. Traditional methods primarily focus on extracting image features, encompassing texture, color, and spatial relationships. This study, however, introduces a scale-based feature image retrieval algorithm. This technique serves as a method for local feature vector extraction, capturing scale angle variations and exhibiting affine invariant characteristics. In assessments, this algorithm consistently outperforms its conventional counterparts, especially in matching scenes from varied viewpoints.

References

[1]

Seidl T, Fries S, Boden B. 2013. MR-DSJ: Distance-Based Self-Join for Large-Scale Vector Data Analysis with MapReduce[J]. BTW.

Google Scholar

[2]

Wairimu J, Gauthier S, Ogana W. 2014. Mathematical Analysis of a Large Scale Vector SIS Malaria Model in a Patchy Environment[J]. Applied Mathematics, 05:1913-1926.

Crossref

Google Scholar

[3]

Yasmin M, Mohsin S, Sharif M. 2014. Intelligent Image Retrieval Techniques: A Survey[J]. Journal of Applied Research & Technology, 14(2):87-103.

Crossref

Google Scholar

[4]

M. A. Hanif, H. Kaur, M. Rakhra and A. Singh. 2022. "Role of CBIR In a Different fields-An Empirical Review", 2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST), 1-7.

Google Scholar

[5]

G. Sérieys, C. Kurtz, L. Fournier and F. Cloppet. 2022. "Text-guided visual representation learning for medical image retrieval systems", 2022 26th International Conference on Pattern Recognition (ICPR), 593-598.

Google Scholar

[6]

K. Shanthi and S. Manimekalai. 2021. "A Survey of Feature Extraction for Pap-Smear Image Classification", Revista Geintec-Gestao Inovacao E Tecnologias, vol. 11, no. 4, 3468-3476.

Crossref

Google Scholar

[7]

A. Sharmaand and P. K. Mishra. 2022. "Performance analysis of machine learning based optimized feature selection approaches for breast cancer diagnosis", International Journal of Information Technology, vol. 14, no. 4, 1949-1960.

Crossref

Google Scholar

Index Terms

Research on a Scale-Based Feature Image Retrieval Algorithm
1. Computing methodologies
  1. Computer graphics

Recommendations

Statistical Characteristics-Based Multi-Scale Image Feature Extraction
ICCIP '23: Proceedings of the 2023 9th International Conference on Communication and Information Processing

Convolutional Neural Networks (CNNs) have improved image feature extraction ability at various scales. However, it fails to match the input features with different importance or complexity into the appropriate feature extraction branches more ...
Rotation and scale invariant wavelet feature for content-based texture image retrieval

This article introduces an effective rotation and scale invariant log-polar wavelet texture feature for image retrieval. The proposed feature is an attempt to enhance the existing content-based image retrieval systems that largely present difficulty in ...
A Textural Feature-Based Image Retrieval Algorithm
ICNC '08: Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 04

In this paper, we propose an effective content-based image retrieval (CBIR) method, based on textural features. Compared with color and shape features, texture features can indicate the spatial distribution of the pixels in an image. Firstly, gray level ...

Comments

Information & Contributors

Information

Published In

EITCE '23: Proceedings of the 2023 7th International Conference on Electronic Information Technology and Computer Engineering

October 2023

1809 pages

ISBN:9798400708305

DOI:10.1145/3650400

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2024

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article
Research
Refereed limited

Conference

EITCE 2023

EITCE 2023: 2023 7th International Conference on Electronic Information Technology and Computer Engineering

October 20 - 22, 2023

Xiamen, China

Acceptance Rates

Overall Acceptance Rate 508 of 972 submissions, 52%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

0
Total Citations
11
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)2

Reflects downloads up to 17 Feb 2025

Other Metrics

View Author Metrics

Citations

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Abstract

References

Index Terms

Recommendations

Statistical Characteristics-Based Multi-Scale Image Feature Extraction

Rotation and scale invariant wavelet feature for content-based texture image retrieval

A Textural Feature-Based Image Retrieval Algorithm

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Login options

Full Access

View options

PDF

eReader

HTML Format

Share

Share this Publication link

Share on social media

Affiliations