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Table 2 Image Name Original Image Segmented Image with modified BFO Hunterman Image Segmentation using RGB… Leena BW Pattern Colored Pattern Dotted Pattern Airplane V1 CONCLUSION It has been observed from the results that the proposed algorithm offers a more resolved thresholding in comparison to any other thresholding method like Otsu or watershed. The image decomposition into its RGB components and computation of threshold in each component image using BFO algorithm prove to be a good tool in order to faithfully segment or threshold the image. The proposed algorithm finds some limitation at the end of time of computation. This is because the algorithm runs three times on the input image in R, G and B components. Further if the size of the image increases, the time may again increase. However, the speed of algorithm can be optimized when running the same on high performance machine. The final threshold value has been computed by taking the mean of the three components thresholds. Further work may be carried out in order to integrate the three thresholds to fine tune the application. REFERENCES [1] Rosenfeld and Kak, Digital Picture Processing. 2, Academic Press, New York, 1982 [2] H. D. Cheng, X. H. Jiang, Y. Sun, and J. L. Wang, “Color image segmentation: Advances and prospects,” Pattern Recognition., Volume 34 Issue 12 December 2011 pp 2259-2281 [3] Alasdair Mc Andrew, An Introduction to Digital Image Processing with Matlab, Cengage learning [4] S.Saadi, A.Kouzou, A.Guessoum, M.Bettayeb “Bacterial Foraging Algorithm for Neutron Radiography Image Quality Improvement” ] 201O 7th International Multi-Conference on Systems, Signals and Devices [5] K. M. Passino, “Biomimicry of bacterial foraging for distributed optimization and control,” IEEE Control Systems Magazine, vol. 22, pp. 52–67, 2002.optimization and control,” Control Systems Magazine, vol. 22, no. 3, pp. 52-67, Jun 2002. [6] Kevin M Passino, “Biomimicry for optimisation,control,automation” Springer-Verlag London,UK 2005 [7] Bakwad KM, Pattnaik SS, Sohi BS, Devi S, Panigrahi BK, Sastri GSVR, “Bacterial Foraging Optimization Technique Cascaded with Adaptive Filter to Enhance Peak Signal to Noise Ratio from Single Image”, IETE Journal of Research, Vol 55 (4), Jul-Aug 2009. www.<strong>ijcer</strong>online.com ||May ||2013|| Page 54
Image Segmentation using RGB… [8] Liu W, Chen H, Chen H, and Chen M, “RFID Network Scheduling Using an Adaptive Bacteria Foraging Algorithm”, Journal of Computer Information Systems (JCIS), Vol. 7(4), 2011, pp. 1238-1245. [9] Sambarta Dasgupta, Swagatam Das “Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications” Studies in Computational intelligence volume 203,2009 pp23-55 www.<strong>ijcer</strong>online.com ||May ||2013|| Page 55
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International Journal of computatio
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