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A Relative Study on the Segmentation Techniques of Image Processing

Venkata Srinivasu Veesam, Bandaru Satish Babu, , ,
Affiliations
Assistant Professor, R.V.R & JC College of Engineering. Andhra Pradesh, India.
:10.22362/ijcert/2017/v4/i5/xxxx [UNDER PROCESS]


Abstract


Citation
Venkata Srinivasu Veesam et.al, “A Relative Study on the Segmentation Techniques of Image Processing”, International Journal of Computer Engineering In Research Trends, 4(5):155-160,May -2017.


Keywords : Image Segmentation, Thresholding, Feature-based clustering, Region based segmentation, Model-based Segmentation, Graph-based Segmentation.

References
[1] Waseem Khan, ”Image Segmentation Techniques: A Survey,” Journal of Image and Graphics, Vol. 1, No. 4, December 2013, available at, http://www.joig.org/uploadfile/2013/1226/20131226051740869.pdf  
[2] Sujata Saini and Komal Arora, ” A Study Analysis on the Different Image Segmentation Techniques,” International Journal of Information & Computation Technology. ISSN 0974-2239 Volume 4, pp. 1445-1452, 2014, available at, http://www.ripublication.com/irph/ijict_spl/ijictv4n14spl_13.pdf
[3] Rajeshwar Dass, Priyanka, and Swapna Devi,” Image Segmentation Techniques,” EJECT Vol. 3, Issue 1, ISSN: 2230-7109 (Online) |  ISSN: 2230-9543 (Print), Jan-March 2012.
[4] Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing,” 2nd ed., Beijing: Publishing House of Electronics Industry, 2007, 
[5] H. G. Kagami and Z. Beige, “Region-Based Detection versus Edge Detection,” IEEE Transactions on Intelligent information hiding and multimedia signal processing, pp. 1217-1221, 2009.
[6] K. K. Singh and A. Singh, “A Study of Image Segmentation Algorithms for Different Types of Images,” International Journal of Computer Science Issues, Vol. 7, Issue 5, 2010.
[7] Hassan Grema Kagami and Zou Beijing, “Region-Based Segmentation versus Edge Detection,” Intelligent Information Hiding and Multimedia Signal Processing, 2009. IIH-MSP '09. Fifth International Conference, pp. 1217 – 1221, DOI: 10.1109/IIH-MSP.2009.13, 2009.
[8] Nikita Sharma, Mahendra Mishra and Manish Shrivastava, “ Colour Image Segmentation Techniques and Issues: An Approach,” International, W. X. Kang, Q. Q. Yang, R. R. Liang, “The Comparative Research on Image Segmentation Algorithms,” IEEE Conference on ETCS, pp. 703-707, 2009.
[9] Muthukrishnan and Radha, “Edge Detection Techniques For Image Segmentation”, International Journal of Computer Science & Information Technology (IJCSIT), Vol 3, No 6, Dec 2011, available at  http://airccse.org/journal/jcsit/1211csit20.pdf
[10]http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/MORSE/threshold.pdf
[11]http://www.ancient-asia-journal.com/articles/10.5334/aa.06113/
[12] Salem Saleh Al-Amri, N.V. Kalyankar and Khamitkar, ” Image Segmentation by Using Threshold Techniques,” Journal Of Computing, Volume 2, Issue 5, ISSN 2151-9617, May 2010, available at https://arxiv.org/ftp/arxiv/papers/1005/1005.4020.pdf 
[13] Santanu Bhowmik and Viki Datta,” A Survey on Clustering Based Image Segmentation,” International Journal of Advanced Research in Computer Engineering & Technology, Volume 1, ISSN: 2278 – 1323, Issue 5, July 2012, available at, http://ijarcet.org/wp-content/uploads/IJARCET-VOL-1-ISSUE-5-280-284.pdf
[14]Sriparna Saha and Sanghamitra Bandyopadhyay”, A new symmetry-based multiobjective clustering technique for the automatic evolution of clusters,” Journal Pattern Recognition, Volume 43, Issue 3, pp 738-751, March 2010.
[15] Lehmann,”Turbo segmentation of textured images,” on Pattern Analysis and Machine Intelligence, Vol: 33, pp: 16 – 29, 2011.
[16] J. Luo, R. T. Cray and Lee, “Incorporation of derivative priors in adaptive Bayesian color image segmentation’’, Proc. ICIP’97, Vol. 3, pp. 58-61, Oct 26-29, 1997.
[17] J. Gao and J. Zhang M. G. Fleming, ”A Novel Multiresolution Color Image Segmentation Technique and its application to Dermatoscopic Image Segmentation,” Image Processing, vol.3, pp.408-411, 2000.  
[18] Tamas Sziranyi, Josiane Zerubia, Laszlo Czuni, David Goldreich and Zoltan Kato, “Image Segmentation Using Markov Random Field Model in Fully Parallel Cellular Network Architectures”, Real-Time Imaging 6, DOI:10.1006/rtim.1998.0159, pp. 195-211 (2000), available at, https://www.inf.u-szeged.hu/~kato/papers/rti2000.pdf
[19] Pedro F. Felzenszwalb and Daniel P. Huttenlocher, “Efficient Graph-Based Image Segmentation,” International Journal of Computer Vision 59(2), pp. 167–181, 2004.


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