Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dekker A. Kohonen Neural Networks for Optimal Colour Quantization. Network: Computation in Neural Systems, 5:351-367, 1994.
Jain A, Murty M, and Flynn P. Data Clustering: A Review. ACM Computing Surveys, 31(3):264-323, 1999.
Jain A and Dubes R. Algorithms for Clustering Data. Prentice Hall, 1988.
Jain A, Duin R, and Mao J. Statistical Pattern Recognition: A Review. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1):4-37, 2000.
Liew A, Leung S, and Lau W. Fuzzy Image Clustering Incorporating Spatial Continuity. In IEE Proceedings Vision, Image and Signal Processing, volume 147, 2000.
Pandya A and Macy R. Pattern Recognition with Neural Networks in C++. CRC Press, 1996.
Everitt B. Cluster Analysis. Heinemann Books, 1974.
Freisleben B and Schrader A. An Evolutionary Approach to Color Image Quantization. In Proceedings of IEEE International Conference on Evolutionary Computation, pages 459-464, 1997.
Wu B and Shi Z. A Clustering Algorithm based on Swarm Intelligence. In Proceedings of the International Conference on Info-tech and Info-net, pages 58-66, 2001.
Zhang B. Generalized K -Harmonic Means - Boosting in Unsupervised Learning. Technical Report HPL-2000-137, Hewlett-Packard Labs, 2000.
Carpineto C and Romano G. A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval. Machine Learning, 24(2):95-122, 1996.
Coello Coello C. An Empirical Study of Evolutionary Techniques for Multiobjective Optimization in Engineering Design. PhD thesis, Tulane University, 1996.
Coello Coello C and Lechuga M. MOPSO: A Proposal for Multiple Objective Particle Swarm Optimization. In Congress on Evolutionary Computation, volume 2, pages 1051-1056, 2002.
Lee C and Antonsson E. Dynamic Partitional Clustering Using Evolution Strategies. In The Third Asia-Pacific Conference on Simulated Evolution and Learning, 2000.
Veenman C, Reinders M, and Backer E. A Cellular Coevolutionary Algorithm for Image Segmentation. IEEE Transactions on Image Processing, 12(3):304-316, 2003.
Judd D, Mckinley P, and Jain A. Large-scale Parallel Data Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(8):871-876, 1998.
Van den Bergh F. An Analysis of Particle Swarm Optimizers. PhD thesis, Department of Computer Science, University of Pretoria, 2002.
Van der Merwe D and Engelbrecht A. Data Clustering using Particle Swarm Optimization. In IEEE Congress on Evolutionary Computation, pages 215-220, 2003.
Davies E. Machine Vision: Theory, Algorithms, Practicalities. Academic Press, 2nd edition, 1997.
Forgy E. Cluster Analysis of Multivariate Data: Efficiency versus Interpretability of Classification. Biometrics, 21:768-769, 1965.
Lumer E and Faieta B. Diversity and Adaptation in Populations of Clustering Ants. In Proceedings of the Third International Conference on Simulation and Adaptive Behavior, pages 501-508, 1994.
Hoppner F, Klawonn F, Kruse R, and Runkler T. Fuzzy Cluster Analysis, Methods for Classification, Data Analysis and Image Recognition. John Wiley & Sons Ltd, 1999.
Maselli F. Multiclass Spectral Decomposition of Remotely Sensed Scenes by Selective Pixel Unmixing. IEEE Transactions on Geoscience and Remote Sensing, 36(5):1809-1819,1998.
Ball G and Hall D. A Clustering Technique for Summarizing Multivariate Data. Behavioral Science, 12:153-155, 1967.
Coleman G and Andrews H. Image Segmentation by Clustering. In Proceedings of IEEE, volume 67, pages 773-785, 1979.
Hamerly G. Learning Structure and Concepts in Data using Data Clustering. PhD thesis, University of California, San Diego, USA, 2003.
Hamerly G and Elkan C. Alternatives to the K -means Algorithm that Find Better Clusterings. In Proceedings of the ACM Conference on Information and Knowledge Management (CIKM-2002), pages 600-607, 2002.
Abbas H and Fahmy M. Neural Networks for Maximum Likelihood Clustering. Signal Processing, 36(1):111-126, 1994.
Frigui H and Krishnapuram R. A Robust Competitive Clustering Algorithm with Applications in Computer Vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(5):450-465, 1999.
Bezdek J. A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2:1-8, 1980.
Bezdek J. Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, 1981.
Braquelaire J and Brun L. Comparison and Optimization of Methods of Color Image Quantization. IEEE Transactions on Image Processing, 6(7):1048-1052, 1997.
Fieldsend J and Singh S. A Multi-objective Algorithm based upon Particle Swarm Optimization, an Efficient Data Structure and Turbulence. In The 2002 UK Workshop on Computational Intelligence, pages 34-44, 2002.
Kennedy J and Eberhart R. Particle Swarm Optimization. In Proceedings of IEEE International Conference on Neural Networks, volume 4, pages 1942-1948, 1995.
Kennedy J and Eberhart R. Swarm Intelligence. Morgan Kaufmann, 2001.
Saghri J, Tescher A, Jaradi F, and Omran M. A Viable End-Member Selection Scheme for Spectral Unmixing of Multispectral Satellite Imagery Data. Journal of Imaging Science and Technology, 44(3):196-203, 2000.
Saghri J, Tescher A, and Omran M. Class-Prioritized Compression of Multispectral Imagery Data. Journal of Electronic Imaging, 11(2):246-256, 2002.
Velho L, Gomes J, and Sobreiro M. Color Image Quantization by Pairwise Clustering. In Proceedings of the Tenth Brazilian Symposium on Computer Graphics and Image Processing, pages 203-207, 1997.
Celenk M. A Color Clustering Technique for Image Segmentation. Computer Vision, Graphics and Image Processing, 52:145-170, 1990.
Omran M, Salman A, and Engelbrecht AP. Image Classification using Particle Swarm Optimization. In Conference on Simulated Evolution and Learning, volume 1, pages 370-374, 2002.
Omran M, Engelbrecht AP, and Salman A. A PSO-based Color Image Quantizer. Special issue of Informatica Journal in multimedia mining in Soft Computing, 29(3):263-271, 2005.
Omran M, Engelbrecht AP, and Salman A. A PSO-based End-Member Selection Method for Spectral Unmixing of Multispectral Satellite Images. International Journal of Computational Intelligence, 2(2):124-132, 2005.
Omran M, Engelbrecht AP, and Salman A. Particle Swarm Optimization Method for Image Clustering. International Journal of Pattern Recognition and Artificial Intelligence, 19(3):297-322, 2005.
Labroche N, Monmarche N, and Venturini G. Visual Clustering based on the Chemical Recognition System on Ants. In Proceedings of the European Conference on Artificial Intelligence, 2002.
Scheunders P. A Genetic C-means Clustering Algorithm Applied to Image Quantization. Pattern Recognition, 30(6), 1997.
Suganthan P. Particle Swarm Optimizer with Neighborhood Optimizer. In Proceedings of the Congress on Evolutionary Computation, pages 1958-1962, 1999.
Krishnapuram R and Keller J. A Possibilistic Approach to Clustering. IEEE Transactions on Fuzzy Systems, 1(2):98-110, 1993.
Krishnapuram R and Keller J. The Possibilistic C-Means algorithm: Insights and Recommendations. IEEE Transactions on Fuzzy Systems, 4(3):385-393, 1996.
Storn R and Price K. Differential Evolution - A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces. Technical Report TR-95-012, International Computer Science Institute, 1995.
Turi R. Clustering-Based Colour Image Segmentation. PhD thesis, Monash University, 2001.
Baek S, Jeon B, Lee D, and Sung K. Fast Clustering Algorithm for Vector Quantization. Electronics Letters, 34(2):151-152, 1998.
Paterlini S and Krink T. Differential Evolution and Particle Swarm Optimization in Partitional Clustering. Computational Statistics and Data Analysis, 50(2006):1220-1247, 2005.
Shafer S and Kanade T. Color Vision, pages 124-131. Wiley, 1987.
Kaukoranta T, FrA˜ ?nti P, and Nevalainen O. A New Iterative Algorithm for VQ Codebook Generation. In International Conference on Image Processing, pages 589-593, 1998.
Kohonen T. Self-Organization and Associative Memory. Springer-Verlag, 3rd edition, 1989.
Hu X. Particle Swarm Optimization: Bibliography. 2004.
Hu X and Eberhart R. Adaptive Particle Swarm Optimization: Detection and Response to Dynamic Systems. In Proceedings of Congress on Evolutionary Computation, pages 1666-1670, 2002.
Rui X, Chang C, and Srikanthan T. On the initialization and Training Methods for Kohonen Self- Organizing Feature Maps in Color Image Quantization. In Proceedings of the First IEEE International Workshop on Electronic Design, Test and Applications, 2002.
Wu X and Zhang K. A Better Tree-Structured Vector Quantizer. In Proceedings IEEE Data Compression Conference, pages 392-401, 1991.
Xiao X, Dow E, Eberhart R, Ben Miled Z, and Oppelt R. Gene Clustering using Self-Organizing Maps and Particle Swarm Optimization. In Proceeding of Second IEEE International Workshop on High Performance Computational Biology, 2003.
Leung Y, Zhang J, and Xu Z. Clustering by Space-Space Filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12):1396-1410, 2000.
Shi Y and Eberhart R. A Modified Particle Swarm Optimizer. In Proceedings of the IEEE International Conference on Evolutionary Computation, pages 69-73, 1998.
Shi Y and Eberhart R. Parameter Selection in Particle Swarm Optimization. In Evolutionary Programming VII: Proceedings of EP’98, pages 591-600, 1998.
Xiang Z. Color Image Quantization by Minimizing the Maximum Inter-cluster Distance. ACM Transactions on Graphics, 16(3):260-276, 1997.
Xiang Z and Joy G. Color Image Quantization by Agglomerative Clustering. IEEE Computer Graphics and Applications, 14(3):44-48, 1994.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Omran, M.G.H., Engelbrecht, A.P., Salman, A. (2006). Particle Swarm Optimization for Pattern Recognition and Image Processing. In: Abraham, A., Grosan, C., Ramos, V. (eds) Swarm Intelligence in Data Mining. Studies in Computational Intelligence, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-34956-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-34956-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34955-6
Online ISBN: 978-3-540-34956-3
eBook Packages: EngineeringEngineering (R0)