Image retrieval based on colour and improved NMI texture features-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Image retrieval based on colour and improved NMI texture features

Published:2019-09-05 Issue:4 Volume:60 Page:491-499
ISSN:0005-1144
Container-title:Automatika
language:en
Short-container-title:Automatika

Author:

Du Anyu¹,Wang Liejun²,Qin Jiwei³

Affiliation:

1. School of Information Science and Engineering, Xinjiang University, Urumchi, People’s Republic of China

2. School of Software Engineering, Xinjiang University, Urumchi, People’s Republic of China

3. School of Education, Shaanxi Normal University, Xi’an, People’s Republic of China

Publisher

Informa UK Limited

Subject

General Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00051144.2019.1645977

Reference8 articles.

1. Content‐based image retrieval system via sparse representation

2. Fusion of color histogram and LBP-based features for texture image retrieval and classification

3. Image NMI Feature Extraction and Retrieval Method Based on Pulse Coupled Neural Networks

4. Local tri-directional patterns: A new texture feature descriptor for image retrieval

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Image Retrieval Using Fusion of Sauvola and Thepade’s Sorted Block Truncation Coding-Based Color Features;Pertanika Journal of Science and Technology;2023-07-13

2. A Framework of a Filtering and Classification Techniques for Enhancing the Accuracy of a Hybrid CBIR System;Mobile Radio Communications and 5G Networks;2022

3. Recent Techniques in Image Retrieval: A Comprehensive Survey;Advances in Intelligent Systems and Computing;2022

4. Content based image retrieval based on weighted fusion of texture and color features derived from modified local binary patterns and local neighborhood difference patterns;Multimedia Tools and Applications;2021-08-06

5. Image Retrieval Using Low Level and Local Features Contents: A Comprehensive Review;Applied Computational Intelligence and Soft Computing;2020-10-22

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3