Image Segmentation Using Suprathreshold Stochastic Resonance
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Image Segmentation Using Suprathreshold Stochastic Resonance

Authors: Rajib Kumar Jha, P.K.Biswas, B.N.Chatterji

Abstract:

In this paper a new concept of partial complement of a graph G is introduced and using the same a new graph parameter, called completion number of a graph G, denoted by c(G) is defined. Some basic properties of graph parameter, completion number, are studied and upperbounds for completion number of classes of graphs are obtained , the paper includes the characterization also.

Keywords: Completion Number, Maximum Independent subset, Partial complements, Partial self complementary.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1071734

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References:


[1] R. C. Gonzales and R. E. Woods, "Digital Image Processing," Reading, MA: Addison Wesley, 1992.
[2] H. D. Cheng, X. H. Jiang, Y. Sun and J. Wang, "Color image segmenta- tion: Advances and prospects," Journal of Pattern Reconition, vol. 34, pp. 2259-2281, 2001.
[3] A. W. Liew, H. Yan and N. F. Law, "Image segmentation based on adaptive cluster prototype estimation," IEEE Trans. Fuzzy Syst., vol. 13, no. 4, pp. 444-453, 2005.
[4] N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern Recognition, vol. 26, no. 9, pp. 1277-1294, 1993.
[5] J. Bruce, T. Balch and M. Veloso, "Fast and Inexpensive Color Image Segmentation for Interactive Robots," in Proc. IEEE/RSJ Intl Conf. Intelligent Robots and Systems, 2000.
[6] W. N Lie, "Automatic target segmentation by locally adaptive image thresholding," IEEE Trans. Image Processing, vol. 4, no. 7, pp. 1036- 1041, July 1995.
[7] Z. Wasik and A. Saffiotti, "Robust Color Segmentation for the RoboCup Domain," in 16th International Conference on Pattern Recognition, vol. 2, pp. 651-654, 2002.
[8] Jia Li , James Z. Wang , Gio Wiedehold, "IRM: integrated region matching for image retrieval," Processings of the eighth ACM inter- national conference on Multimedia, Marina del Rey, California, United States, pp. 147-156, October 2000.
[9] Sittichote Janpaiboon and Sanya Mitaim, "Adaptive Stochastic Reso- nance in Color Object Segmentation," IEEE International Joint Confer- ence on neural Networks, vol. 1, pp. 2508-2515, 2006.
[10] J. B. T. M. Roerdink and A. Meijster, "The watershed transform: definitions, algorithms, and parallelization strategies," In Fundamenta Informaticae, vol. 41, pp. 187-228, 2000.
[11] Kyung-Seok SEO, Chang-Joon PARK, Sang-Hyun CHOİ Heung-Moon CHOI, "Context-Free Marker-Controlled Watershed Transform for Ef- ficient Multi-Object Detection and Segmentation," Publication IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences, vol. E84-A, no.6, pp. 1392-1400, 2001.
[12] Ruey-Ming Chao, Hsien-Chu Wu, Zi-Chun Chen, "Image segmentation by automatic histogram thresholding," in Proceedings of the 2nd Inter- national Conference on Interaction Sciences: Information Technology, Culture and Human, pp. 136-141, November 24-26, 2009, Seoul, Korea.
[13] http://www.flickr.com/photos/80327698@N00/3166736209/