A Comparative Study on Image Segmentation using Maximal Similarity Region Merging

Authors

  • Akansha Sanghi Department of CSE/IT, ITM Universe, Gwalior, India
  • Amit Pandey Department of CSE/IT, ITM Universe, Gwalior, India

DOI:

https://doi.org/10.37591/josettt.v2i3.524

Abstract

Segmentation is a low level process concerned with images partitioning through defining discontinuity or similarity or equivalently, through finding boundaries or edges. Image segmentation is a mechanism used for an image divide into numerous segments. The main objective is to create the image meaningful and more simple, so as to modification the an image optimization into the something that is additional important and easier to study various approaches of image segmentation have been established through scholars in order to make images smooth and easy to evaluate. This paper presents a literature review on the technique of image segmentation this paper presents a summary of specific well-known image segmentation methods.

Keywords: Image segmentation, ANN based image segmentation, fuzzy based image segmentation, edge based image segmentation

Cite this Article
Akansha Sanghi, Amit Pandey. A Comparative Study on Image Segmentation using Maximal Similarity Region Merging. Journal of Software Engineering Tools & Technology Trends. 2015; 2(3): 1–8p.

References

Sharif M, Mohsin S, Jamal MJ, et al. Illumination normalization preprocessing for face recognition. In Proc. International Conference on Environmental Science and Information Application Technology. 2010; 2: 44–47p.

Yasmin M, Sharif M, Masood S., et al. Brain image enhancement-A survey. World Applied Sciences Journal. 2012; 17: 1192–1204p.

Raut S, Raghuvanshi M, Dharaskar R, et al. Image segmentation-A state-of-art survey for prediction. In Proc. International Conference on Advanced Computer Control. 2009; 420–424p.

Seerha G. Review on recent image segmentation techniques. International Journal on Computer Science and Engineering. 2009.

Acharya J, Gadhiya S, Raviya K. Segmentation techniques for image analysis: A review. International Journal of Computer Science and Management Research. 2013; 2: 2278–733p.

Rastgarpour M, Shanbehzadeh J. Application of AI techniques in medical image segmentation and novel categorization of available methods and tools. Proceedings of the International

MultiConference of Engineers and Computer Scientists. 2011; 1: 16–18p.

Rahini KK, Sudha SS. Review of image segmentation techniques: A survey. International Journal of Advanced Research in Computer Science and Software Engineering. 2014; 4(7): 842–845p.

Zhang YJ. An overview of image and video segmentation in the last 40 years. Proceedings of the 6 th International Symposium on Signal Processing and Its Applications. 2001; 144–151p.

Wahba Marian. An automated modified region growing technique for prostate segmentation in trans-rectal ultrasound images. Master's Thesis, Department of Electrical and Computer Engineering; 2009.

ChangY, Li X. Adaptive image region growing. IEEE Trans. on Image Processing. Vol. 3, No. 6, 1994.

Singh KK, Singh A. A study of image segmentation algorithms for different types of images. International Journal of Computer Science. 2010; 7(5): 414p.

Kang WX, Yang QQ, Liang RR. The comparative research on image segmentation algorithms. IEEE Conference on ETCS. 2009; 703–707p.

Rastgarpour M, Shanbehzadeh J. Application of AI techniques in medical image segmentation and novel categorization of available methods and tools. Proceedings of the International MultiConference of Engineers and Computer Scientists. 2011; 1.

Muhammad Waseem Khan. A Survey: image segmentation techniques. International Journal of Future Computer and Communication. 2014; 3(2): 89–93p.

Rozy Kumari, Narinder Sharma. A study on the different image segmentation technique. International Journal of Engineering and Innovative Technology (IJEIT). 2014; 4(1): 284–289p.

Khandare ST, Akshay D Isalkar. a survey paper on image segmentation with thresholding. IJCSMC. 2014; 3(1): 441– 446p.

Savita Agrawal, Deepak Kumar Xaxa. Survey on image segmentation techniques and color models. (IJCSIT) International Journal of Computer Science and Information Technologies. 2014; 5(3): 3025 –3030p.

Downloads

Published

2015-10-23

Issue

Vol. 2 No. 3 (2015)

Section

Research Articles

License

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

  • I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
  • I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
  • I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
  •  I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. ________________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.