Commenced in January 2007
Paper Count: 30135
Manipulation of Image Segmentation Using Cleverness Artificial Bee Colony Approach
Abstract:Image segmentation is the concept of splitting the images into several images. Image Segmentation algorithm is used to manipulate the process of image segmentation. The advantage of ABC is that it conducts every worldwide exploration and inhabitant exploration for iteration. Particle Swarm Optimization (PSO) and Evolutionary Particle Swarm Optimization (EPSO) encompass a number of search problems. Cleverness Artificial Bee Colony algorithm has been imposed to increase the performance of a neighborhood search. The simulation results clearly show that the presented ABC methods outperform the existing methods. The result shows that the algorithms can be used to implement the manipulator for grasping of colored objects. The efficiency of the presented method is improved a lot by comparing to other methods.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1126005Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 922
 J. S. Hu and Y. J. Chang, “Calibration of an eye-to-hand system using a laser pointer on hand and planar constrains,” in Proc. IEEE Int. Conf. Robot. Autom., Shanghai, China, 2011, pp. 982–987.
 J. Ning, L. Zhang, D. Zhang, and C. Wu, “Interactive image segmentation by maximal similarity based region merging,” Pattern Recognit., vol. 43, no. 2, pp. 445–456, Feb. 2010.
 H. Li and C. Shen, “Interactive color image segmentation with linear programming,” Mach. Vis. Appl., vol. 21, no. 4, pp. 03–412, Jun.2010.
 J. F. Vigueras and M. Rivera, “Registration and interactive planar segmentation for stereo images of polyhedral scenes,” Pattern Recognit., vol. 43, no. 2, pp. 494–505, Feb. 2010.
 Robinson, Y.H. and Rajaram, M., 2015. Energy-aware multipath routing scheme based on particle swarm optimization in mobile ad hoc networks. The Scientific World Journal, 2015.
 A. Noma, A. B. V. Graciano, R. M. C., Jr, L. A. Consularo, and I. Bloch, “Interactive image segmentation by matching attributed relational graphs,” Pattern Recognition., vol. 45, no. 3, pp. 1159–1179, Mar.2012.
 M. Pardowitz, R. Haschke, J. Steil, and H. Ritter, “Gestalt-based action segmentation for robot task learning,” in Proc. 8th IEEE-RAS Int. Conf. Humanoid Robot., Daejeon, Korea, Dec. 2008, pp. 347–352.
 Robinson, Y.H., Rajaram, M. and Raju, H., 2015. Evolutionary Program Based Approach for Manipulator Grasping Color Objects. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 8, no. 12, pp.2141-2146.
 W. R. Tan, C. S. Chan, P. Yogarajah, and J. Condell, “A fusion approach for efficient human skin detection,” IEEE Trans. Ind. Informat., vol. 8, no. 1, pp. 138–147, Feb. 2012.
 D. Schiebener, A. Ude, J. Morimotot, T. Asfour, and R. Dillmann, “Segmentation and learning of unknown objects through physical interaction,” in Proc. 11th IEEE-RAS Int. Conf. Humanoid Robot., Bled, Slovenia, Oct. 2011, pp. 500–506.
 K. Y. Chan, C. K. F. Yiu, T. S. Dillon, S. Nordholm, and S. H. Ling, “Enhancement of speech recognitions for control automation using an intelligent particle swarm optimization,” IEEE Trans. Ind. Informat., vol. 8, no. 4, pp. 869–879, Nov. 2012.
 F. Tao, D. Zhao, Y. Hu, and Z. Zhou, “Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system,” IEEE Trans. Ind. Informat., vol. 4, no. 4, pp.315–327, Nov. 2008.
 Harold Robinson, Y., &Rajaram, M. (2015), “Establishing pairwise keys using key Predistribution schemes for sensor networks”, World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 9, no.2, pp. 608–612.
 Harold Robinson, Y., & Rajaram, M. (2015). “Trustworthy link failure recovery algorithm for highly dynamic mobile adhoc networks”, World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol.9, no.2, 233–236.
 Dervis Karaboga, Bahriye Basturk” Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems”. Vol no.5, pp 39:459–471 April 2009.
 Princess, P.J.B. and Robinson, Y.H., 2015.Discrete and Stationary Adaptive Sub-Band Threshold Method for Improving Image Resolution. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 9(4), pp.957-960.