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Novel Approach of New Dualistic Enhancement for Digital Image Segmentation using FCM

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Amandeep Kaur, Rakesh Kumar, Sukjot Kaur

Amandeep Kaur, Rakesh Kumar and Sukjot Kaur. Novel Approach of New Dualistic Enhancement for Digital Image Segmentation using FCM. International Journal of Computer Applications 158(10):5-10, January 2017. BibTeX

	author = {Amandeep Kaur and Rakesh Kumar and Sukjot Kaur},
	title = {Novel Approach of New Dualistic Enhancement for Digital Image Segmentation using FCM},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {158},
	number = {10},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {5-10},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2017912760},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Image segmentation plays important role in the biomedical images. The process of image segmentation is defined as the technique via which a given photograph is segmented into several parts in order to further analyze every of these components present in the photo [9]. In segmentation, without a doubt image is represented into greater understandable form. Segmentation essentially used to hit upon the gadgets, obstacles and other applicable facts in the digital snap shots. There are exceptional tactics to enforce segmentation like threshold, clustering and remodel strategies etc. [10]. The reason for the popularity of image segmentation is because of its importance in the area of image processing. The prime task of the researchers working in this field is to develop a method for efficient and better image segmentation. There are certain factors that affect the process of image segmentation like the intensity of image to be segmented, color, type and the noise present in the image [12]. No algorithm has been developed till date that could keep a look at all the above listed factors and then segment the image effectively so that all the problems that can come in the way of image segmentation can be avoided. The algorithm development for effective image segmentation is still a big research that will take place in the area of image processing. In this paper a new technique is proposed. This technique is capable of covering the lacking points of traditional techniques or algorithms. In this work DSIHE is implemented along with fuzzy C-Mean segmentation technique in order to enhance the quality and performance of the technique.


  1. Alzate, C (April, 2007).Image Segmentation using a Weighted Kernel PCA Approach to Spectral Clustering.IEEE, CIISP 2007, pp 208-2013.
  2. Amanpreet Kaur(December 2014).A Review Paper on Image Segmentation and its Various Techniques in Image Processing.IJSR, Volume 3 Issue 12, pp 12-14.
  3. Ashraf A. Aly.research review for digital image segmentation techniques.ijcsit Vol 3, No 5, Oct 2011, pp 99-106.
  4. C.Sriramakrishnan (May, 2012).Performance Analysis of Advanced Image Segmentation Techniques.International Journal of Computer Applications, Volume 45– No.7, pp 13-18.
  5. Dibya Jyoti Bora (September, 2014).A Novel Approach Towards Clustering Based Image Segmentation.IJESE, Volume-2 Issue-11, pp 6-10.
  6. H C Sateesh Kumar,(February 2009).Automatic Image Segmentation using Wavelets.
  7. Hakeem Aejaz Aslam (March, 2013).A New Approach to Image Segmentation for Brain Tumor detection using Pillar K-means Algorithm.IJARCCE, Vol. 2, Issue 3, pp 1429-1436.
  8. Hui Zhang.Image Segmentation Evaluation.A Survey of Unsupervised Methods, Image.
  9. JITENDRA MALIK.Contour and Texture Analysis for Image Segmentation.International Journal of Computer Vision 43(1), 7–27, 2001.
  10. Khang Siang Tan (January, 2011) .Color image segmentation using histogram thresholding – Fuzzy C-means hybrid approach.ELSEVIER, VOl:44, Issue:1, pp 1-15.
  11. M. Erd(2014).Segmentation: A New View of Image Segmentation and Registration.IEEE.
  12. M. Jogendra Kumar(September 2014).review on image segmentation techniques.ijsret, Volume 3, Issue 6, pp 992-997.
  13. Mei Yeen Choong .An Image Segmentation using Normalised Cuts in Multistage Approach.IJSSST, pp 10-16.
  14. Muhammad Waseem Khan et al(April 2014).A Survey: Image Segmentation Techniques.International Journal of Future Computer and Communication, Vol. 3, No. 2 , pp 89-93.
  15. N. Senthilkumaran( May 2009).Edge Detection Techniques for Image Segmentation – A Survey of Soft Computing Approaches. International Journal of Recent Trends in Engineering, Vol. 1, No. 2, pp 250-254.
  16. Pushpa .R. Suri, Mahak (June 2012).Image Segmentation With Modified K-Means Clustering Method.
  17. Rafika Harrabi (May, 2012).Color image segmentation using multi-level thresholding approach and data fusion techniques: application in the breast cancer cells images.Springer, pp 1-12.
  18. Rajiv Kumar (December, 2011).Image Segmentation using Discontinuity-Based Approach.IJMIP, Volume 1, pp 72-78.
  19. Rohan Kandwal(April 2014).Review: Existing Image Segmentation Techniques.IJARCSSE, Volume 4, Issue 4 , pp 153-156.
  20. S Sapna Varshney(December 2009).Comparative study of image segmentation techniques and object matching using segmentation. IEEE, Methods and Models in Computer Sc2ience, 2009. ICM2CS 2009. Proceeding of International Conference on, pp 1-6.
  21. S.Dhanalakshmi(September 2012).A New Method for Image Segmentation.IJARCSSE, Volume 2, Issue 9, pp 293-299.
  22. Sharon Alpert.Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration.
  23. Shuai Zheng.Dense Semantic Image Segmentation with Objects and Attributes.
  24. V. Dey.A review on image segmentation techniques with remote sensing perspective.iaprs,Vol. XXXVIII, Part 7A, pp 31-42.
  25. Varshali Jaiswal (December, 2013).A Survey of Image Segmentation based on Artificial Intelligence and Evolutionary Approach.IOSR-JCE, Volume 15, Issue 3, PP 71-78.


Segmentation; Enhancement; Normalization Euclidean Distance; Signal to Noise Ratio; C-Mean Segmentation.

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