Skip to content
Research Article Open access CC BY 4.0

A New Approach of Content Based Image Retrieval Using Color and Texture Features

Md. Shahadat Hossain, Md. Rafiqul Islam

Current Journal of Applied Science and Technology · pp. 1–16 · Published 7 Jun 2017

10.9734/BJAST/2017/33326

Abstract

The dramatic development of multimedia technology, and the use of image capturing equipment have increased the number of images worldwide which are needed to be available. For this purpose, there are many general processes of image retrieval of which are Text based image retrieval (TBIR), Content based images retrieval (CBIR). While retrieving images using text-based approach, all the images are needed to be annotated manually which is time consuming. To be get the image retrieval process rid of this complexity content based approach was introduced. There are several processes of CBIR system. Here a new method of CBIR has been proposed which is based on both texture features and color features. Here, HSV histogram, Autocorrelogram, and color moment have been used to extract the color features. On the other hand, for the purpose of the extraction of texture features, Wavelet transformation, and Gabor wavelet transformation have been used. For implementing the process, a GUI has been designed at first. For every category searching, the elapsed time is calculated, and compared with the existing methods.

CBIR system color moment autocorrelogram Gabor filter Euclidian distance Manhattan distance precision recall texture feature

References (25)

  1. 1 Revolutionizing Cybersecurity Audit through Artificial Intelligence Automation: A Comprehensive Exploration [DOI]
  2. 2 IRM [DOI]
  3. 3 Large-scale malware indexing using function-call graphs [DOI]
  4. 4 Content-based image retrieval using color moment and Gabor texture feature [DOI]
  5. 5 Content Based Image Retrieval Using Embedded Neural Networks with Bandletized Regions [DOI]
  6. 6 Embedding neural networks for semantic association in content based image retrieval [DOI]
  7. 7 A Novel Image Retrieval Based on a Combination of Local and Global Histograms of Visual Words [DOI]
  8. 8 Comparison of Content Based Image Retrieval Systems Using Wavelet and Curvelet Transform [DOI]
  9. 9 Content based image retrieval using statistical features of color histogram [DOI]
  10. 10 MSIDX: Multi-Sort Indexing for Efficient Content-Based Image Search and Retrieval [DOI]
  11. 11 Spatial Weighting for Bag-of-Features Based Image Retrieval [DOI]
  12. 12 Effective hashing for large-scale multimedia search [DOI]
  13. 13 Managing multimedia information in database systems [DOI]
  14. 14 An intelligent decision support system for digital preservation [DOI]
  15. 15 Content Based Image Retrieval Using SVM Algorithm [DOI]
  16. 16 Signature Based Approach For Image Retrieval Using Color Histogram And Wavelet Transform
  17. 17 Image Retrieval based on Integration between Color and Geometric Moment Features
  18. 18 Wavelet Based Fingerprint Image Enhancement [DOI]
  19. 19 Content-Based Image Retrieval System in Medical Applications
  20. 20 Image retrieval using the combination of text-based and content-based algorithms [DOI]
  21. 21 Content Based Image Retrieval by Using the Bayesian Algorithm to Improve and Reduce the Noise from an Image
  22. 22 AN EFFICIENT CONTENT BASED IMAGERETRIEVAL USING LOCAL TETRAPATTERN
  23. 23 A Comparative Analysis of Feature Sets for Image Classification Using Back Propagation Neural Network [DOI]
  24. 24 International Journal of Engineering and Computer Science [DOI]
  25. 25 International Journal on Digital Libraries [DOI]

Cited by 16

A new method of construction waste classification based on two-level fusion

Lin Song, Hui-xuan Zhao, Zong-Fang Ma · PLoS ONE · 2022

A Smart Content-Based Image Retrieval Approach Based on Texture Feature and Slantlet Transform

Hakeem Imad Mhaibes, Qahtan Makki Shallal, May Hattim Abood · International journal of electrical and computer engineering systems · 2022

Improving the Performance of CBIR Using XGBoost Classifier with Deep CNN-Based Feature Extraction

Jasman Pardede, Benhard Sitohang, Saiful Akbar · International Conference on Data and Software Engineering · 2019

A Random Vector Functional Link Network Based Content Based Image Retrieval

S. Mary, A. Sasithradevi, S. M. Roomi · 2019 Fifth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) · 2019

Boosting-Based Relevance Feedback for CBIR

Jasman Pardede, Benhard Sitohang, Saiful Akbar · International Conference on Data and Software Engineering · 2018

Ayeyarwady River Regions Detection and Extraction System from Google Earth Imagery

Ei Moh Moh Aung, T. Tint · 2018 IEEE International Conference on Information Communication and Signal Processing (ICICSP) · 2018

Re-weighting Relevance Feedback in HSV Quantization for CBIR

Jasman Pardede, Benhard Sitohang, Saiful Akbar · Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing · 2018

Showing 12 of 16 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

81

Page views

0

PDF downloads

37

Outbound clicks

16

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.