CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Edge Detection in Color Images using RGB Color Model

by E. Boopathi Kumar, V. Thiagarasu
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 9
Year of Publication: 2018
Authors: E. Boopathi Kumar, V. Thiagarasu
10.5120/ijca2018916120

E. Boopathi Kumar, V. Thiagarasu . Edge Detection in Color Images using RGB Color Model. International Journal of Computer Applications. 180, 9 ( Jan 2018), 6-11. DOI=10.5120/ijca2018916120

@article{ 10.5120/ijca2018916120,
author = { E. Boopathi Kumar, V. Thiagarasu },
title = { Edge Detection in Color Images using RGB Color Model },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 180 },
number = { 9 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number9/28888-2018916120/ },
doi = { 10.5120/ijca2018916120 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:00:09.646943+05:30
%A E. Boopathi Kumar
%A V. Thiagarasu
%T Edge Detection in Color Images using RGB Color Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 9
%P 6-11
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Edge Detection is an important technique in image processing and it is the process of grouping an image into units that are consistent with respect to one or more features. Edge detection using gray images has lot of methods to segment and it has several set of algorithms to represent it. But the images produce more information in scenes i.e., color images have few set of methods to segment it. So, this paper represent color image edge detection methods in the literature and getting to prepare novel segmentation method by extracting the color channels in the RGB image into three with combined form of masking, filtering and Thresholding methods. Otsu method is one of the best and famous Thresholding method used in color image segmentation and it uses various combinations of masks to scan over the image to detect the correct boundary. Otsu method divides the segmentation tasks in two or more phases and provides the results better along with different phases. In the same way this paper discusses about RGB color model and fuzzy membership functions method and particularly about the usage of fuzzy membership functions which are used to create mask with some sort of rules based on RGB channel extraction to scan the separated channel image with few combinations and include Threshold method and filtering for further to produce the output image in well enhanced manner.

References
  1. Anil K Jain (2014), “Fundamentals of Digital Image Processing”, ISBN 978-81-203-0929-6, Pearson Education.
  2. Rafael C Gonzalez and Richard E Woods (2013), “Digital image processing”, ISBN 978-81-317-2695-2, Pearson Education.
  3. Rafael C Gonzalez, Richard E Woods and Steven L Eddins (2011), “Digital image processing using MATLAB”, ISBN – 13: 978-0-07-070262-2, Tata McGraw Hill Education.
  4. Firas Ajil Jassim, Fawzi H. Altaani, “Hybridization of Otsu Method and Median Filter for Color Image Segmentation”, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-3, Issue-2, May 2013.
  5. A.Kalaivani, Dr.S.Chitrakala, “Automatic Color Image Segmentation”, International Conference on Science, Engineering and Management Research (ICSEMR 2014), ©2014 IEEE.
  6. Md. Habibur Rahman, Md. Rafiqul Islam, “Segmentation of Color Image using Adaptive Thresholding and Masking with Watershed Algorithm”, 978-1-4799-0400-6/13/ ©2013 IEEE.
  7. Navkirat Kaur, V. K. Banga, Avneet Kaur, “Image Segmentation Based on Color”, International Journal of Research in Engineering and Technology, Volume: 02, Issue: 11, Nov-2013
  8. Rafael Guillermo Gonzalez, Junli Tao, “Generalization of Otsu’s Binarization into Recursive Color Image Segmentation”, 978-1-5090-0357-0/15/, © 2015 IEEE.
  9. Suryakant, Neetu Kushwaha, “Edge Detection using Fuzzy Logic in Matlab”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 4, April 2012.
  10. Shikha Bharti, Sanjeev Kumar, “An Edge Detection Algorithm based on Fuzzy Logic”, International Journal of Engineering Trends and Technology, Volume 4, Issue 3, 2013.
  11. Mehul Thakkar, Prof. Hitesh Shah, “Edge Detection Techniques Using Fuzzy Thresholding”, 978-1-4673-0126-8/ 2011, IEEE.
  12. Song Gao, Chengcui Zhang, and Wei-Bang Chen, “An Improvement of Color Image Segmentation through Projective Clustering”, IEEE IRI 2012, August 8-10, 2012. Jan Puzicha and Serge Belongie, “Model–based Halftoning for Color Image Segmentation”, UC Berkeley, Department of Computer Science, December 2002.
  13. Soumya Dutta, Bidyut B. Chaudhuri, “Homogenous Region based Color Image Segmentation”, Proceedings of the World Congress on Engineering and Computer Science, ISBN: 978-988-18210-2-7, Volume 2, October 2009.
  14. E. Boopathi Kumar, M. Sundaresan, “Edge Detection Using Trapezoidal Membership Function Based on Fuzzy‘s Mamdani Inference System”, IEEE, 2014.
  15. E. Boopathi Kumar, M. Sundaresan, “Fuzzy Inference System based Edge Detection using Fuzzy Membership Functions”, International Journal of Computer Applications, ISSN: 0975 – 8887, Volume 112, Issue: 4, February 2015.
  16. Xiaohua Tian, Wang sheng Yu, “Color Image Segmentation Based on Watershed Transform and Feature Clustering”, IEEE 2016.
  17. Ajaya Kumar Dash, Banshidhar Majhi, “Image Segmentation Using Fuzzy Based Histogram Thresholding”, IEEE 2015.
  18. Sneha M. Mahajan, Yogita K. Dubey, “Color Image Segmentation Using Kernalized Fuzzy C-means Clustering”, Fifth International Conference on Communication Systems and Network Technologies, IEEE 2015.
  19. E. Boopathi Kumar, V. Thiagarasu, “Segmentation using Fuzzy Membership Functions: An Approach”, IJCSE, ISSN 2347-2693, Pages: 101-105, Volume 5, Issue 3, March 2017.
  20. E. Boopathi Kumar, V. Thiagarasu, “Segmentation using Fuzzy Logic in Color Images Based on Membership Functions”, IJESRT, ISSN 2277 – 9655, Pages: 38-45, Volume 6, Issue 6, June 2017.
  21. Huang-Chia Shih, En-Rui Liu, “Automatic Reference Color Selection for Adaptive Mathematical Morphology and Application in Image Segmentation”, IEEE Transactions On Image Processing, 2016.
  22. Chaohui Lü, Xingyun Yang and Sha Qi, “Color Image Segmentation Based on the Ant Colony Algorithm”, th International Congress on Image and Signal Processing, IEEE, 2015.
  23. Simranjit Singh Walia, Gagandeep Singh, “Color based Edge detection techniques– A review”, International Journal of Engineering and Innovative Technology, Volume 3, Issue 9, March 2014.
  24. E. Boopathi Kumar, V. Thiagarasu, “Segmentation using Masking Methods in Color Images: an Approach”, International Journal of Engineering Sciences & Research Technology (IJESRT), ISSN 2277 – 9655, Pages: 104-110, Volume 6, Issue 2, February 2017.
  25. E. Boopathi Kumar, V. Thiagarasu, “Comparison and Evaluation of Edge Detection using Fuzzy Membership Functions”, International Journal on Future Revolution in Computer Science & Communication Engineering (IJFRCSCE), ISSN: 2454 – 4248, Pages: 149 – 153, Volume 3, Issue 8, August 2017.
  26. Er. Manpreet Kaur, Ms. Sumeet Kaur, “A New Approach To Edge Detection Using Rule Based Fuzzy Logic”, Volume 2, No. 9, September 2011.
  27. Emmanuel Joy and J. Dinesh Peter, “Tracking of Unique Colored Objects: A Simple, Fast Visual Object Detection and Tracking Technique”, E.B. Rajsingh et al. (eds.), Informatics and Communication Technologies for Societal Development, Springer India 2015.
  28. M. Borsotti, P. Campadelli, R. Schettini, “Quantitative evaluation of color image segmentation results”, Pattern Recognition Letters 19 (1998) 741–747
  29. H.D. Cheng, X.H. Jiang, Y. Sun, Jingli Wang, “Color image segmentation: advances and prospects”, Pattern Recognition 34 (2001) 2259-2281.
  30. E. Boopathi Kumar, V. Thiagarasu, “Color Image Edge Detection Using Fuzzy Membership Functions”, International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), ISSN: 2394-4099, Pages: 970 – 975, Volume 3, Issue 6, September – October 2017.
Index Terms

Computer Science
Information Sciences

Keywords

Color Image Edge Detection RGB Color Model Color Channel Extraction Fuzzy Inference System Triangular Membership Function Trapezoidal Membership Function.

Powered by PhDFocusTM