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The Evaluation Criterion for Color Image Segmentation Algorithms

References MORAVČÍK, T.: Image Segmentation in Programming Environment MATLAB, OWD International PhD Workshop, Wisla, 17-20 October 2009, pp. 469-470. ZHANG, Y. J.: Advances in Image and Video Segmentation, IRM Press, USA, 2006. SHAPIRO, L. G.—STOCKMAN, G. C.: Computer Vision, Prentice Hall, New Jersey, 2001. SMEULDERS, A. W. M.—WORRING, M.—SANTINI, S.—GUPTA, A.—JAIN, R.: Content-Based Image Retrieval at the End of the Early Years, IEEE Transactions on

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Analysing the Methods of Dzongkha Word Segmentation

References [1] G. van Driem, “Language Policy in Bhutan,” presented at conference “Bhutan: a traditional order and the forces of change”, London, UK, March 1993. [2] D. C. Chhoeden et al., “Dzongkha Text-to-Speech Synthesis System - Phase II,” in Conference on Human Language Technology for Development, May 2-5, 2011, Alexandria, Egypt, pp. 148-153. [3] S. Norbu et al., “Dzongkha Word Segmentation,” in 8th Workshop on Asian Language Resources, August 21-22, 2010, Beijing, China, pp. 95-102. [4] H

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Comparison of minimization methods for nonsmooth image segmentation

References 1. T. Chan and L. Vese, Active contours without edges, IEEE Transactions on Image Processing, vol. 10, no. 2, pp. 266-277, 2001. 2. D. Mumford and J. Shah, Optimal approximations by piecewise smooth functions and associated variational problems, Communications on Pure and Applied Mathematics, vol. 45, no. 2, pp. 577-685, 1989. 3. T. Chan, S. Esedofiglu, and M. Nikolova, Algorithms for finding global minimizers of image segmentation and denoising models, SIAM Journal on Applied Mathematics, vol. 66, no

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Intelligent Segmentation of Medical Images Using Fuzzy Bitplane Thresholding

References [1] Armato, S.G., Giger, M.L., Moran, C.J. (1999). Computerized detection of pulmonary nodules on CT scans. Radio Graphics, 19, 1303-1311. [2] Hu, S., Huffman, E.A., Reinhardt, J.M. (2001). Automatic lung segmentation for accurate quantification of volumetric X-Ray CT images. IEEE Transactions on Medical Imging, 20 (6), 490-498. [3] Grau, V., Mewes, A.U., Alcaniz, M., Kikinis, R., Warfield, S.K. (2004). Improved watershed transform for medical image segmentation using prior information. IEEE

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Evaluating the performance of various segmentation techniques in industrial radiographs

References 1. Ananth, A. G. Classification ofa Satellite Rural Image Based on Fractal Dimension Using Box Counting Method. - International Journal of Computer Applications, Vol. 16, 2011, No 5, 45-48. 2. Wu, B.-F., Y.-L. Chen, C.-C. Chiu. A New Region-Based Segmentation Method for Complex Document Image Analysis. - International Journal of Computational Science and Engineering, Vol. 1, 2005, 34-44. 3. Funck, Y. Zhon g, D. A. Butler, C. Brunner, J. B. Forrer. Image Segmentation Algorithms Applied to Wood Defect

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Proposed Concept of Segmentation of Traditional Japanese Emissive Market for Managing Tourist Promotion of Mediterranean Countries

identity and place image. Paper presented at the European Regional Science Association Congress, Jönköping, Sweden. Bluesun hotels, 2013. Marketing information system Bluesun hotels. Butler, R., 2000. Modelling tourism development, Evolution growth and decline, Tourism, Development and Growth. London: Routledge. Cheong Jang, S., Morrison, A. M., and O’Leary, J. T., 2002. Benefit segmentation of Japanese pleasure travellers to USA and Canada: selecting target markets based on the profitability and risk of individual market

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Review of Printed Fabric Pattern Segmentation Analysis and Application

References [1] Gonzalez, R. C., Woods, R. E. (1992). Digital image processing. Addison-Wesley (Reading). [2] Lo, W. Y., Puchalski, S. M. (2008). Digital image processing. Veterinary Radiology & Ultrasound, 49, S42-S47. [3] Rafsanjani, M. K., Varzaneh, Z. A., Chukanlo, N. E. (2012). A survey of hierarchical clustering algorithms. The Journal of Mathematics and Computer Science, 5(3), 229-240. [4] Burney, S. A., Tariq, H. (2014). K-means cluster analysis for image segmentation. International Journal of Computer Applications, 96(4), 1

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Methodology for the Evaluation of the Algorithms for Text Line Segmentation Based on Extended Binary Classification

References Du, X., Pan, W., Bui, T.D. (2009). Text line segmentation in handwritten documents using Mumford-Shah model. Pattern Recognition , 42 (12), 3136-3145. Likforman Sulem, L., Zahour, A., Taconet, B. (2007). Text line segmentation of historical documents: a survey. International Journal on Document Analysis and Recognition , 9 (2), 123-138. Amin, A., Wu, S. (2005). Robust skew detection in mixed text/graphics documents. In Proceedings of International Conference on

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Enhanced CNN Based Electron Microscopy Image Segmentation

-ECCV, Vol. 1 , 1996, 546-555. 11. Macke, J. H., N. Maack, R. Gupta, W. Denk, B. Scholkopf, A. Borst. Contour- Propagation Algorithms for Semi-Automated Reconstruction of Neural Processes. - Journal of Neuroscience Methods, Vol. 167 , 2008, No 2, 349-357. 12. Grossberg, S., E. Mingolla. Neural Dynamics of Perceptual Grouping: Textures, Boundaries, and Emergent Segmentations. - Attention, Perception, & Psychophysics, Vol. 38 , 1985, No 2, 141-171. 13. Beck, J. Effect of Orientation and of Shape Similarity on Perceptual

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Business Client Segmentation in Banking Using Self-Organizing Maps

References 1. Agarwal, J., Malhotra, N. K., Bolton, R. N. 2010. A cross-national and cross-cultural approach to global market segmentation: An application using consumers’ perceived service quality. Journal of International Marketing 18(3): 18-40. 2. Anderson, W.T., Cox, E.P., Fulcher, D.G. 1976. Bank Selection Decisions and Market Segmentation. Journal of Marketing 40(1): 40-45. 3. Assunçao, J. 2013. Eliminating entry barriers for the provision of banking services: Evidence from ‘banking correspondents’ in

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