Review Study on Digital Image Processing and Segmentation
American Journal of Computer Science and Technology
Volume 2, Issue 4, December 2019, Pages: 68-72
Received: Oct. 15, 2019; Accepted: Nov. 9, 2019; Published: Dec. 31, 2019
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Authors
Puja Shashi, Computer Science Department, Jain University, Bangalore, India
Suchithra R, HOD IT Department, Jain University, Bangalore, India
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Abstract
Image segmentation is in fact one of the most fundamental approach of digital image processing. In image processing, segmentation playa an important role. It may be defined as partitioning an image into meaning full regions or objects. In other words we can say that process of segmentation keeps on dividing an image into its constitute sub parts. The level to which the subdivision is carried on depends on type of problem to be solved by researchers. This segmentation process continues unless area of interest is isolated. Set of segment or set of contours that are extracted from the image is the main result of image segmentation. There are various application of image segmentation like locating tumors or other pathologies, measuring tissue volume, surgery aided by computer, treatment and planning, study of various anatomical structure, locating objects in satellite images, fingerprint. There are various types of generalized algorithm and methodology that are developed for image segmentation. Some common technique of image segmentation such as edge detection, thresh holding, region growing and clustering are taken for this study. In fact segmentation algorithm are based on two properties similarity and discontinuity. This paper concentrates on the various methods that are widely used to segment the image.
Keywords
Segmentation, Digital Image Processing, Edge Detection, Thres Holding, Region Growing, Clustering
To cite this article
Puja Shashi, Suchithra R, Review Study on Digital Image Processing and Segmentation, American Journal of Computer Science and Technology. Vol. 2, No. 4, 2019, pp. 68-72. doi: 10.11648/j.ajcst.20190204.14
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Shapiro, Linda G. & Stockman. George C. (2002). “Computer vision”. Prentice Hall. ISBN 0-13-030796-3.
[2]
P. Singh, P and R. S. Chadha, A Novel Approach to Image Segmentation, International Journal of Advanced Research in Computer Science and Software Engineering Research Paper, 2013.
[3]
S. Zhu, X. Xia, Q. Zhang, and K. Belloulata, "An image segmentation algorithm in image processing based on threshold segmentation," in Proc. Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, SITIS'0., pp. 673-678, 2007.
[4]
A. Xu, L. Wang, S. Feng, and Y. Qu, "Threshold-based level set method of image segmentation," in Proc. 3rd International Conference 92 International Journal of Future Computer and Communication, Vol. 3, No. 2, April 2014 on Intelligent Networks and Intelligent Systems (ICINIS), pp. 703-706, 2010.
[5]
M. Yasmin, M. Sharif, S. Masood, M. Raza, and S. Mohsin, "Brain image enhancement-A survey," World Applied Sciences Journal, vol. 17, pp. 1192-1204, 2012.
[6]
E. R. Davies, Machine Vision: theory, algorithms, practicalities, 1997.
[7]
R. Gurcan, I. Erer and S. Kent, An edge detection method using 2-D autoregressive lattice prediction filters for remotely sensed images, In Geoscience and Remote Sensing Symposium, 2004, IGARSS'04, Proceedings of 2004 IEEE International, IEEE, September, 2004, Vol. 6, pp. 4219- 4222.
[8]
R. Yogamangalam and B. Karthikeyan, Segmentation techniques comparison in image processing, International Journal of Engineering and Technology (IJET), 2013, 5 (1), 307-313.
[9]
J. Serra and P. Salembier, “Connected operators and pyramids,” in Image Algebra and Morphological Image Processing IV, vol. 2030 of Proceedings of SPIE, San Diego, Calif, USA, July 1993, pp. 65–76.
[10]
Senthilkumaran, N., Rajesh, R.: Edge detection techniques for image segmentation—A survey of soft computing approaches. Int. J. Recent Trends Eng. 1 (2), 250–254 (2009).
[11]
Hore, S., et al.: An integrated interactive technique for image segmentation using stack based seeded region growing and thresholding. Int. J. Electr. Comput. Eng. 6.6, 2773 (2016) 9. Smistad, E., et al.: Medical image segmentation on GPUs–A comprehensive review. Med. Image Anal. 20.1, 1–18 (2015).
[12]
D. Ziou and S. Tabbone, Edge detection techniques-an overview, Pattern Recognition and Image Analysis C/C of Raspoznavaniye Obrazov I Analiz Izobrazhenii, 8, 1998, 537-559.
[13]
T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu, An efficient k-means clustering algorithm: Analysis and implementation. IEEE transactions on pattern analysis and machine intelligence, 2002, 24 (7), 881-892.
[14]
Chen, Z. et al.: Image segmentation via improving clustering algorithms with density and distance. Proc. Comput. Sci. 55, 1015–1022 (2015).
[15]
Satish Kumar, Raghavendra Srinivas, “A Study on Image Segmentation and its Methods”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 9, September 2013.
[16]
P. Sravani et al, “ A Survey on Image Segmentation Techniques and Clustering”, International Journal of Advance Research in Computer Science and Management Studies, Special Issue, December 2013.
[17]
H. P. Narkhede, “Review of Image Segmentation Techniques”, International Journal of Science and Modern Engineering (IJISME) ISSN: 2319-6386, Volume-1, Issue-8, July 2013.
[18]
Rajeshwar Dass, Priyanka, Swapna Devi, “Image Segmentation Techniques”, IJECT Vol. 3, Issue 1, Jan.-March 2012. 1452 Sujata Saini and Komal Arora.
[19]
Nikita Sharma, Mahendra Mishra, Manish Shrivastava, “COLOUR IMAGE SEGMENTATION TECHNIQUES AND ISSUES: AN APPROACH”, International Journal of Scientific & Technology Research Volume 1, Issue 4, May 2012.
[20]
PunamThakare, “A Study of Image Segmentation and Edge Detection Techniques”, International Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 2 Feb 2011.
[21]
V. Dey, Y. Zhang, M. Zhong, “A REVIEW ON IMAGE SEGMENTATION TECHNIQUES WITH REMOTE SENSING PERSPECTIVE”, July 5–7, 2010, IAPRS, Vol. XXXVIII, Part 7A.
[22]
N. Senthilkumaran and R. Rajesh, “Edge Detection Techniques for Image Segmentation – A Survey of Soft Computing Approaches”, International Journal of Recent Trends in Engineering, Vol. 1, No. 2, May 2009.
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