Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods

Bahtiar Imran

doi:doi:10.11648/j.ajnna.20190501.14

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Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods

Bahtiar Imran

Published in American Journal of Neural Networks and Applications (Volume 5, Issue 1)

Received: 22 April 2019 Accepted: 24 June 2019 Published: 4 July 2019

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Abstract

As the development of data storage technology from various sources of information then increasingly cause problems in the search and processing, of course with the existence of this problem will be feared can cause big losses. Various existing search techniques have not been able to provide clear results between query testing and training. To overcome this problem required a Content-Based Image Retrieval (CBIR) approach which is a technique for content-based image search. In this study using texture and color information from image training to present the results both in query testing and database training using Tamura texture method features Gabor texture features. Before displaying the query results first the image testing in extracts using Tamura texture features and Gabor texture features to get the feature values used for image testing and then matching it with the value of features available in the training database. The application used in this research is an application from LIRE and database image that used is database from image. orig. the results obtained in this research is, the application of texture Tamura method features and Gabor texture features based on the features and colors can provide significant results between image testing and image training.

Published in	American Journal of Neural Networks and Applications (Volume 5, Issue 1)
DOI	10.11648/j.ajnna.20190501.14
Page(s)	23-27
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

CBIR, Feature, Tamura Texture Feature, Texture, Matching

References

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[2]	M. D. Agaputra, et al., “Pencarian Citra Digital Berbasiskan Konten dengan Ekstraksi Fitur HSV, ACD, dan GLCM, vol. 8, pp. 8-13.
[3]	B. M. S and Naik. M. B., “Content Based Image Retrieval Using Color and Texture Content,” International Journal of Computer Trends and Technology (IJCTT), vol. 48, June 2017, pp. 78-84.
[4]	N. V. M. K. Raja and K. S. Banu, “Content Bases Image Search And Retrieval Using Indexing By KMeans Clustering Technique,” International Journal of Advanced Research in Computer and Communication Engineering, vol. 2, May 2013, pp. 2181-2189.
[5]	R. B and K. R. Chandran., “Content Based Medical Image Retrieval with Texture Content Using Gray Level Co-occurrence Matrix and K-Means Clustering Algorithms”, Journal of Computer Science, Vol. 8, 2012, pp. 1070-1076.
[6]	I. Hastuti, et al., “Content Based Image Retrieval Berdasarkan Fitur Bentuk Menggunakan Metode Gradient Vector Flow,” Seminar Nasional Informatika UPN Veteran Yogyakarta, 2009, pp. 140-145.
[7]	T. Mehyar and O. J. Atoum., "An Enhancement on Content-Based Image Retrieval using Color and Texture Features," Journal of Emerging Trends in Computing and Information Sciences, vol. 3, pp. 488-496.
[8]	A. Halim, et al., “Aplikasi Image Retrieval Menggunakan Kombinasi Metode Color Moment dan Gabor Texture, “JSM STMIK Mikroskil, vol. 14, October 2013, pp. 109-117.
[9]	S. V. B and J. M. David., "Content Based Image Retrieval: Classification Using Neural Networks," The International Journal of Multimedia & Its Applications (IJMA), vol. 6, October 2014, pp. 31-44.
[10]	Wicaksono. Y, et al., “Color and Texture Feature Extraction Using Gabor Filter – Local Binary Patterns for Image Segmentation with Fuzzy C-Means,” Journal of Intelligent Systems, Vol. 1, No. 1, February 2015.
[11]	Jain. N and Salankar. S. S., “Content Based Image Retrieval Using Gabor Texture Feature and Color Histogram”, International Journal of Enhanced Research in Science Technology & Engineering, Vol. 3 Issue 9, Sept.-2014, pp: 97-102.
[12]	Kumari. B., “CBIR Systems: Results of Feature Extraction with Color Feature Comparison with Standard Database”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 5, Issue 11, November 2017.
[13]	Singha. M., “Content Based Image Retrieval using Color and Texture,” Signal & Image Processing: An International Journal (SIPIJ), Vol. 3, No. 1, February 2012.
[14]	Thawari. P. B. and Janwe. N. J., “CBIR BASED ON COLOR AND TEXTURE”, International Journal of Information Technology and Knowledge Management, Vol. 4, No. 1, pp. 129-132.
[15]	Yadav. A. K. r, et al., “Survey on Content-based Image Retrieval and Texture Analysis with Applications”, International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 7, No. 6 (2014), pp. 41-50.

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APA Style

Bahtiar Imran. (2019). Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods. American Journal of Neural Networks and Applications, 5(1), 23-27. https://doi.org/10.11648/j.ajnna.20190501.14

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ACS Style

Bahtiar Imran. Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods. Am. J. Neural Netw. Appl. 2019, 5(1), 23-27. doi: 10.11648/j.ajnna.20190501.14

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AMA Style

Bahtiar Imran. Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods. Am J Neural Netw Appl. 2019;5(1):23-27. doi: 10.11648/j.ajnna.20190501.14

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@article{10.11648/j.ajnna.20190501.14,
  author = {Bahtiar Imran},
  title = {Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods},
  journal = {American Journal of Neural Networks and Applications},
  volume = {5},
  number = {1},
  pages = {23-27},
  doi = {10.11648/j.ajnna.20190501.14},
  url = {https://doi.org/10.11648/j.ajnna.20190501.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20190501.14},
  abstract = {As the development of data storage technology from various sources of information then increasingly cause problems in the search and processing, of course with the existence of this problem will be feared can cause big losses. Various existing search techniques have not been able to provide clear results between query testing and training. To overcome this problem required a Content-Based Image Retrieval (CBIR) approach which is a technique for content-based image search. In this study using texture and color information from image training to present the results both in query testing and database training using Tamura texture method features Gabor texture features. Before displaying the query results first the image testing in extracts using Tamura texture features and Gabor texture features to get the feature values used for image testing and then matching it with the value of features available in the training database. The application used in this research is an application from LIRE and database image that used is database from image. orig. the results obtained in this research is, the application of texture Tamura method features and Gabor texture features based on the features and colors can provide significant results between image testing and image training.},
 year = {2019}
}

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TY  - JOUR
T1  - Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods
AU  - Bahtiar Imran
Y1  - 2019/07/04
PY  - 2019
N1  - https://doi.org/10.11648/j.ajnna.20190501.14
DO  - 10.11648/j.ajnna.20190501.14
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 23
EP  - 27
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20190501.14
AB  - As the development of data storage technology from various sources of information then increasingly cause problems in the search and processing, of course with the existence of this problem will be feared can cause big losses. Various existing search techniques have not been able to provide clear results between query testing and training. To overcome this problem required a Content-Based Image Retrieval (CBIR) approach which is a technique for content-based image search. In this study using texture and color information from image training to present the results both in query testing and database training using Tamura texture method features Gabor texture features. Before displaying the query results first the image testing in extracts using Tamura texture features and Gabor texture features to get the feature values used for image testing and then matching it with the value of features available in the training database. The application used in this research is an application from LIRE and database image that used is database from image. orig. the results obtained in this research is, the application of texture Tamura method features and Gabor texture features based on the features and colors can provide significant results between image testing and image training.
VL  - 5
IS  - 1
ER  -

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Author Information

Bahtiar Imran

Sekolah Tinggi Manajemen Informatika Komputer Mataram (STMIK Mataram), Mataram, Indonesia

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APA Style

Bahtiar Imran. (2019). Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods. American Journal of Neural Networks and Applications, 5(1), 23-27. https://doi.org/10.11648/j.ajnna.20190501.14

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ACS Style

Bahtiar Imran. Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods. Am. J. Neural Netw. Appl. 2019, 5(1), 23-27. doi: 10.11648/j.ajnna.20190501.14

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AMA Style

Bahtiar Imran. Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods. Am J Neural Netw Appl. 2019;5(1):23-27. doi: 10.11648/j.ajnna.20190501.14

Copy | Download

@article{10.11648/j.ajnna.20190501.14,
  author = {Bahtiar Imran},
  title = {Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods},
  journal = {American Journal of Neural Networks and Applications},
  volume = {5},
  number = {1},
  pages = {23-27},
  doi = {10.11648/j.ajnna.20190501.14},
  url = {https://doi.org/10.11648/j.ajnna.20190501.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20190501.14},
  abstract = {As the development of data storage technology from various sources of information then increasingly cause problems in the search and processing, of course with the existence of this problem will be feared can cause big losses. Various existing search techniques have not been able to provide clear results between query testing and training. To overcome this problem required a Content-Based Image Retrieval (CBIR) approach which is a technique for content-based image search. In this study using texture and color information from image training to present the results both in query testing and database training using Tamura texture method features Gabor texture features. Before displaying the query results first the image testing in extracts using Tamura texture features and Gabor texture features to get the feature values used for image testing and then matching it with the value of features available in the training database. The application used in this research is an application from LIRE and database image that used is database from image. orig. the results obtained in this research is, the application of texture Tamura method features and Gabor texture features based on the features and colors can provide significant results between image testing and image training.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Content-Based Image Retrieval Based on Texture and Color Combinations Using Tamura Texture Features and Gabor Texture Methods
AU  - Bahtiar Imran
Y1  - 2019/07/04
PY  - 2019
N1  - https://doi.org/10.11648/j.ajnna.20190501.14
DO  - 10.11648/j.ajnna.20190501.14
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 23
EP  - 27
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20190501.14
AB  - As the development of data storage technology from various sources of information then increasingly cause problems in the search and processing, of course with the existence of this problem will be feared can cause big losses. Various existing search techniques have not been able to provide clear results between query testing and training. To overcome this problem required a Content-Based Image Retrieval (CBIR) approach which is a technique for content-based image search. In this study using texture and color information from image training to present the results both in query testing and database training using Tamura texture method features Gabor texture features. Before displaying the query results first the image testing in extracts using Tamura texture features and Gabor texture features to get the feature values used for image testing and then matching it with the value of features available in the training database. The application used in this research is an application from LIRE and database image that used is database from image. orig. the results obtained in this research is, the application of texture Tamura method features and Gabor texture features based on the features and colors can provide significant results between image testing and image training.
VL  - 5
IS  - 1
ER  -

Copy | Download