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Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval

L. Haldurai1 , V. Vinodhini2

Section:Research Paper, Product Type: Journal Paper
Volume-3 , Issue-11 , Page no. 11-15, Nov-2015

Online published on Nov 30, 2015

Copyright © L. Haldurai , V. Vinodhini . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: L. Haldurai , V. Vinodhini, “Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.11, pp.11-15, 2015.

MLA Style Citation: L. Haldurai , V. Vinodhini "Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval." International Journal of Computer Sciences and Engineering 3.11 (2015): 11-15.

APA Style Citation: L. Haldurai , V. Vinodhini, (2015). Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval. International Journal of Computer Sciences and Engineering, 3(11), 11-15.

BibTex Style Citation:
@article{Haldurai_2015,
author = { L. Haldurai , V. Vinodhini},
title = {Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2015},
volume = {3},
Issue = {11},
month = {11},
year = {2015},
issn = {2347-2693},
pages = {11-15},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=717},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=717
TI - Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval
T2 - International Journal of Computer Sciences and Engineering
AU - L. Haldurai , V. Vinodhini
PY - 2015
DA - 2015/11/30
PB - IJCSE, Indore, INDIA
SP - 11-15
IS - 11
VL - 3
SN - 2347-2693
ER -

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Abstract

Content Based Image Retrieval (CBIR) is a challenging method of capturing relevant image from a large storage space. This paper comprise of image features such as color and texture, which is intended to use in image retrieval. These features are extracted using fuzzy approaches. Numerous methods have been introduced in image retrieval systems. However, those methods have its drawbacks. In this paper novel system architecture for CBIR system which combines techniques includes CBIR and fuzzy based feature extraction, indexing procedure as well as genetic algorithm. This proposed approach is found to be very effective and efficient while comparing to previous methods and approaches in image retrieval in terms of retrieving most relevant images with less computational time.

Key-Words / Index Term

Image Retrieval, Parallel indexing, Content Based image Retrieval (CBIR), R Tree, FCTH, Fitness Score

References

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