The week's pick
Reseach Article
Image Segmentation using MSNCut Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 162 - Number 3 |
| Year of Publication: 2017 |
| Authors: Basavaprasad B. |
10.5120/ijca2017913313
|
Basavaprasad B. . Image Segmentation using MSNCut Algorithm. International Journal of Computer Applications. 162, 3 ( Mar 2017), 27-30. DOI=10.5120/ijca2017913313
Abstract
In this paper a hybrid technique for the segmentation of image has been proposed and it is named as MSNCut technique. Here image segmentation is the process of dividing the given image into number of regions that possess similar properties such as color, texture and intensity which are useful for the image analysis. The image is generic here, in other words image may be tree, river, building, medical or any general image. In this proposed method first the input image is pre-processed by mean shift algorithm to divide it into its constituent regions. Then the resultant image is represented as a bi-partite graph and finally the resultant graph (image) is processed under normalized cut to classify the image into meaningful classes.
References
- Malik J and Shi J, "Normalized Cuts and Image Segmentation", IEEE transactions on pattern analysis and machine intelligence, vol. 22, no. 8, 2000.
- Nida M. Zaitoun, Musbah J and Aqel, "Survey on Image Segmentation Techniques", International Conference on Communication, Management and Information Technology (ICCMIT), 2015.
- Nameirakpam D, Khumanthem M and Yambem J. C, "Image Segmentation using K-means Clustering Algorithm and Subtractive Clustering Algorithm", Eleventh International Multi-Conference on Information Processing, 2015.
- Cheng and Yizong, “Mean Shift, Mode Seeking and Clustering””, An IEEE Transaction on Pattern Analysis and Machine Intelligence, Volume: 17, Issue:8, pp:790-799, 1995.
- Basavaprasad B and Ravi M, "Enhanced Color Image Segmentation by Graph Cut Method in General and Medical Image", Lecture Notes in Bioengineering, Advancements of Medical Electronics, Proceedings of the First International Conference, ICAME, 2015.
- Shi J and Malik J, “Image Segmentation and the Normalized Cuts", Machine Intelligence and Pattern Analysis, an IEEE Transactions, Volume 22, 2000.
- Basavaprasad B, Ravindra S Hegadi, "Color Image Segmentation Using Adaptive GrowCut Method", International Conference on Advanced Computing Technologies and Applications (ICACTA), 2015
- Fulkerson D and Ford L, “Flow in networks”, Princeton University Press, 1962.
- Koschan Aand Skarbek W, "A Survey on Color Image Segmentation", Technical Report, Tech. University of Berlin, 1994.
Index Terms
Keywords