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Reseach Article

Edge Detection in Color Images - A Comparative Study

by Hanumanthappa M, S Regina Lourdhu Suganthi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 5
Year of Publication: 2014
Authors: Hanumanthappa M, S Regina Lourdhu Suganthi
10.5120/17367-7891

Hanumanthappa M, S Regina Lourdhu Suganthi . Edge Detection in Color Images - A Comparative Study. International Journal of Computer Applications. 99, 5 ( August 2014), 5-7. DOI=10.5120/17367-7891

@article{ 10.5120/17367-7891,
author = { Hanumanthappa M, S Regina Lourdhu Suganthi },
title = { Edge Detection in Color Images - A Comparative Study },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 5 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 5-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number5/17367-7891/ },
doi = { 10.5120/17367-7891 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:23.268654+05:30
%A Hanumanthappa M
%A S Regina Lourdhu Suganthi
%T Edge Detection in Color Images - A Comparative Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 5
%P 5-7
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The ability to detect edges from an image plays a key role in solving many problems related to computer vision. Extracting appropriate features from an image is a great challenge in the context of content based image retrieval. Some important points in an image could be used to describe the features of an object. To recognize objects from an image, it is essential that the features extracted from an image are invariant due to noise and illumination. Such points lie in high contrast regions such as edges of an object. Generally, a color image is converted to gray scale image to detect the edges of objects. In this paper two color spaces namely RGB and HSV have been considered. These color spaces individually are combined with gray plane and the effect has been discussed. It is evident from the results that by either OR-ing the R, G, B planes with the grayscale plane or by OR-ing S, V planes with the grayscale plane more edges could be detected.

References
  1. Anil K Jain, "Fundamentals of Digital Image Processing", PHI Learning Private Limited, 2011, pg 347-353.
  2. D G Lowe, "Distinctive Image features from scale invariant key points", International Journal of Computer Vision, Vol. 60, no 2, pp 99-110, 2004.
  3. Junding Sun, Guoliang Fan, Xiaosheng Wu, "New Local Edge Binary Patterns For Image Retrieval ", ICIP 2013, 4014 - 4018.
  4. Li-li Huang, Jin Tang,Si-bao Chen, Chris Ding and Bin Luo, "An efficient algorithm for feature selection and feature correlation", IScIDE, volume 7751 of Lecture Notes in Computer Science, page 639-646. Springer, 2012.
  5. Madhura C, Dheeraj D, "Feature Extraction for Image Retrieval using Color Spaces and GCLM", International Journal of Innovative Technology and Exploring Engineering (IJITEE), ISSN : 2278-3075, Vol. 3, Issue -2, July 2013.
  6. Ruba A. A. Salamah, "Efficient Content Based Image Retrieval", Thesis submitted to Islamic University – Gaza, Deanery of Higher Studies, 2010.
  7. Yannis Manolopoulos, Yannis Theodoridis, Vassilis J. Tsotras, "Spatial Access Methods", Advances in database systems, Vol 17, 2000, pp 117-139.
  8. Yu Jin-ping, Huang Xi-mei and Xia Xiao-yun, "Image Data Mining Technology of Multimedia", Future Computing, Communication, Control and Management Lecture Notes in Electrical Engineering Volume 144, 2012, pp 379-385.
  9. Zhou Wang, Member, Alan Conrad Bovik,, Hamid Rahim Sheikh and Eero P. Simoncelli,"Image Quality Assessment: From Error Visibility to Structural similarity", IEEE Transactions on Image Processing, Vol. 13, No. 4, April 2004.
Index Terms

Computer Science
Information Sciences

Keywords

HSV (Hue Saturation Value) LEBP RGB (Red Green Blue) SAM