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An Efficient Approach toward Color Image Segmentation with Combined Effort of Soft Clustering and Region based Techniques using L Channel of LAB Color Space

by Dibya Jyoti Bora, Anil Kumar Gupta, Fayaz Ahmad Khan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 12
Year of Publication: 2015
Authors: Dibya Jyoti Bora, Anil Kumar Gupta, Fayaz Ahmad Khan
10.5120/ijca2015906685

Dibya Jyoti Bora, Anil Kumar Gupta, Fayaz Ahmad Khan . An Efficient Approach toward Color Image Segmentation with Combined Effort of Soft Clustering and Region based Techniques using L Channel of LAB Color Space. International Journal of Computer Applications. 128, 12 ( October 2015), 39-45. DOI=10.5120/ijca2015906685

@article{ 10.5120/ijca2015906685,
author = { Dibya Jyoti Bora, Anil Kumar Gupta, Fayaz Ahmad Khan },
title = { An Efficient Approach toward Color Image Segmentation with Combined Effort of Soft Clustering and Region based Techniques using L Channel of LAB Color Space },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 12 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 39-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number12/22928-2015906685/ },
doi = { 10.5120/ijca2015906685 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:21:28.591609+05:30
%A Dibya Jyoti Bora
%A Anil Kumar Gupta
%A Fayaz Ahmad Khan
%T An Efficient Approach toward Color Image Segmentation with Combined Effort of Soft Clustering and Region based Techniques using L Channel of LAB Color Space
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 12
%P 39-45
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Finding an efficient approach for color image segmentation is always sought by the researchers in the color image processing research. We have different clustering based and region based methods for the same. But still there arises the requirement of an optimal method. In this paper, a new approach for color image segmentation is proposed. Here the segmentation is carried out on the L channel of LAB color space. The input color image is first converted from RGB to LAB. Then L channel is extracted from the LAB converted image and sent as input to FCM algorithm. After this initial segmentation, the segmented image is filtered by sobel filter. The filtered image is then segmented by Meyer’s Watershed algorithm to produce the final segmented image of the original image. The results of the proposed approach are found efficient when the same are analyzed in terms of MSE and PSNR. Also the segmented images are found free from over segmentation.

References
  1. Chris Solomon, Toby Breckon , “Fundamentals of Digital Image Processing”, ISBN 978 0 470 84472 4
  2. R. M. Haralick, L. G.Shapiro, “Image Segmentation Techniques”,CVGIP, vol. 29, 1985,pp. 100-132.
  3. S. M. Aqil Burney, Humera Tariq, “ K-Means Cluster Analysis for Image Segmentation”, International Journal of Computer Applications (0975 – 8887) Volume 96– No.4, June 2014, pp. 1-8.
  4. Amanpreet Kaur Bhogal, Neeru Singla,Maninder Kaur, “Color image segmentation using k-means clustering algorithm”, International Journal on Emerging Technologies 1(2), 2010,pp. 18-20.
  5. D.J. Bora, A.K. Gupta, “Clustering Approach Towards Image Segmentation: An Analytical Study”, IJRCAR,Vol2,Issue 7,July 2014, pp. 115-124
  6. D.J. Bora, A.K. Gupta, F.A. Khan, “ Comparing the Performance of L*A*B* and HSV Color Spaces with Respect to Color Image Segmentation”, International Journal of Emerging Technology and Advanced Engineering, Volume 5, Issue 2, February 2015, pp. 192-203.
  7. C Mythili, V.kavitha, “Color Image Segmentation using ERKFCM”, International Journal of Computer Applications 41(20), March 2012, pp.21-28.
  8. Juraj Horvath, "Image Segmentation using Fuzzy C-means", SAMI 2006.
  9. Indah Soesanti,Adhi Susanto,Thomas Sri Widodo,Maesadji Tjokronagoro, “Optimized Fuzzy Logic Application For MRI Brain Images Segmentation”, International Journal of Computer Science & Information Technology (IJCSIT) Vol 3, No 5, Oct 2011, pp. 137-146.
  10. Le Capitaine H, Frélicot C, “A fast fuzzy c-means algorithm for color image segmentation”,  In EUSFLAT-LFA 2011, Aix-les-Bains, France, 18–22 July 2011. Paris: Atlantis; 2011, pp. 1074–1081.
  11. D.J. Bora, A.K. Gupta, “A Novel Approach Towards Clustering Based Image Segmentation”, International Journal of Emerging Science and Engineering (IJESE)ISSN: 2319–6378, Volume-2 Issue-11, September 2014,pp. 6-10.
  12. Lamia Jaafar Belaid, Walid Mourou, “Image Segmentation: A Watershed Transformation Algorithm”, Image Anal Stereol, 2009;28, pp.93-102
  13. Rahman, M.H., Islam, M.R., "Segmentation of color image using adaptive thresholding and masking with watershed algorithm," Informatics, Electronics & Vision (ICIEV), 2013 International Conference on , vol., no., pp.1,6, 17-18 May 2013
  14. Amit Chaudhary , Tarun Gulati, “Segmenting Digital Images Using Edge Detection”, International Journal of Application or Innovation in Engineering & Management, Volume 2, Issue 5, May 2013, pp. 319-323.
  15. Hunter, RichardSewall (July 1948). "photoelectric color-difference meter". Josa 38 (7): 661. (Proceedings of the winter meeting of the optical society of America)
  16. Hunter, RichardSewall (December 1948). "Accuracy, precision, and stability of new photo-electric color-difference meter". Josa 38 (12): 1094. (Proceedings of the thirty-third annual meeting of the optical society of America)
  17. CIELAB
  18. http://dba.med.sc.edu/price/irf/Adobe_tg/models/cielab.html
  19. J. C. Bezdek ,"Pattern Recognition with Fuzzy Objective Function Algorithms", Plenum Press, New York, 1981.
  20. D.J. Bora, A.K.Gupta, “Impact of Exponent Parameter Value for the Partition Matrix on the Performance of Fuzzy C Means Algorithm”, arXiv preprint arXiv:1406.4007
  21. Irwin Sobel, 2014, History and Definition of the Sobel Operator
  22. Raman Maini, Dr. Himanshu Aggarwal, “Study and Comparison of Various Image Edge Detection Techniques, “International Journal of Image Processing (IJIP), Jan-Feb 2009, Volume (3) Issue (1), pp.1-11.
  23. S. A. Salem, N. V. Kalyankar and S. D. Khamitkar, "Image Segmentation By Using Edge Detection", (IJCSE) International Journal On Computer Science And Engineering, vol. 2, no. 3, 2010,pp. 804-807.
  24. Jos B.T.M. Roerdink ,Arnold Meijster, “The Watershed Transform: Definitions, Algorithms and Parallelization Strategies”, Fundamenta Informaticae 41 (2001) 187–228 1 IOS Press, pp. 1-40.
  25. MATLABNotes,http://www.mathworks.de/company/newsletters/news_ notes/win02/watershed.html
  26. Meyer, Fernand, "Topographic distance and watershed lines," Signal Processing, Vol. 38, July 1994, pp. 113-125.
  27. MATLAB Demo Images
  28. http://www.mathworks.in/products/image
  29. Berkeley Segmentation Dataset: Images
  30. http://www.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/BSDS300/html/dataset/images.html
  31. T. Veldhuizen. "Measures of image quality," 2010,
  32. http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/VELDHUIZEN/node18.html
Index Terms

Computer Science
Information Sciences

Keywords

Color Image Segmentation FCM LAB Sobel Filter and Watershed Algorithm

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