Simultaneous Separation of Low Level Features in Color Images using Orthogonal Polynomials
R. Krishnamoorthy1 , S. Thennavan2 , R.G. Harini3 , K.K. Manisha Narayani4
Section:Research Paper, Product Type: Journal Paper
Volume-06 ,
Issue-04 , Page no. 162-166, May-2018
Online published on May 31, 2018
Copyright © R. Krishnamoorthy, S. Thennavan, R.G. Harini , K.K. Manisha Narayani . 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 Citation
IEEE Style Citation: R. Krishnamoorthy, S. Thennavan, R.G. Harini , K.K. Manisha Narayani, “Simultaneous Separation of Low Level Features in Color Images using Orthogonal Polynomials,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.04, pp.162-166, 2018.
MLA Citation
MLA Style Citation: R. Krishnamoorthy, S. Thennavan, R.G. Harini , K.K. Manisha Narayani "Simultaneous Separation of Low Level Features in Color Images using Orthogonal Polynomials." International Journal of Computer Sciences and Engineering 06.04 (2018): 162-166.
APA Citation
APA Style Citation: R. Krishnamoorthy, S. Thennavan, R.G. Harini , K.K. Manisha Narayani, (2018). Simultaneous Separation of Low Level Features in Color Images using Orthogonal Polynomials. International Journal of Computer Sciences and Engineering, 06(04), 162-166.
BibTex Citation
BibTex Style Citation:
@article{Krishnamoorthy_2018,
author = {R. Krishnamoorthy, S. Thennavan, R.G. Harini , K.K. Manisha Narayani},
title = {Simultaneous Separation of Low Level Features in Color Images using Orthogonal Polynomials},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {06},
Issue = {04},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {162-166},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=374},
publisher = {IJCSE, Indore, INDIA},
}
RIS Citation
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=374
TI - Simultaneous Separation of Low Level Features in Color Images using Orthogonal Polynomials
T2 - International Journal of Computer Sciences and Engineering
AU - R. Krishnamoorthy, S. Thennavan, R.G. Harini , K.K. Manisha Narayani
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 162-166
IS - 04
VL - 06
SN - 2347-2693
ER -




Abstract
In this paper, a new method for simultaneous separation of features in color images using Orthogonal Polynomials is proposed. The low-level features,edge and texture present in the color image under analysis are extracted simultaneously in frequency domain usingOrthogonal Polynomials Transformation. The transformed coefficientsobtained from Orthogonal Polynomials Transformation are categorized into color coefficients, texture coefficients and edge coefficients based on the linear contrast due to Orthogonal Polynomials Transformation in different coordinate axes. A Simplified Gradient Measure approach (SGM approach) is used to extract the edge and texture part of the color image from the categorized coefficients simultaneously after careful examination and representation of color textures. The proposed method is tested with various standard color texture images. The results obtained using this proposed feature separation method is encouraging.
Key-Words / Index Term
Edge extraction, Feature extraction, Orthogonal Polynomials Transformation, Textureextraction
References
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