Literature

Books

• Fuzzy Mathematical Approach to Pattern Recognition, Pal, S.K., Madjumadar, D. D., 1986

• Fuzzy Models for Pattern Recognition, Bezdek, J.C., Pal, S.K., 1992

• Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition, Chi, Z., Yan, H., Pahm, T., 1996

• Fuzzy Cluster Analysis, Höppner, F., Klawonn, F., Kruse, R., 1997

• Fuzzy Image Processing: Introduction in Theory and Applications,  Tizhoosh, Hamid R., 1997 (in German!)

• Fuzzy Models and Algorithms for Pattern Recognition and Image Processing, James C. Bezdek (Editor), James Keller, Raghu Krisnapuram, Nikhil Pal, 1999

• Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing, Sankar K. Pal, Sushmita Mitra, 1999

• Fuzzy Techniques in Image Processing, Etienne E. Kerre, Mike Nachtegael , 2000

• Fuzzy Classifier Design, Ludmila I. Kuncheva, J. Kacprzyk (Editor), 2000

• Neuro-Fuzzy Pattern Recognition, H Bunke (Editor), A. Kandel (Editor), 2001

• Pattern Recognition in Soft Computing Paradigm, Nikhil R. Pal (Editor), 2001

• Fuzzy Filters for Image Processing, M. Nachtegael, D. Van der Weken, D. Van De Ville & E.E. Kerre (Editors), 2002

Papers

On Fuzzy Geometry

Rosenfeld, A. (1979): Fuzzy Digital Topology, Information and Control 40, pp. 76-87.

Rosenfeld, A. (1983): On connectivity properties of grayscale pictures, Pattern Recognition, Vol. 16, pp. 47-50.

Rosenfeld, A. (1984a): The diameter of a fuzzy set, Fuzzy Sets and Systems, Vol. 13, pp. 241-246.

Rosenfeld, A. (1984b): The Fuzzy Geometry of Image Subsets, Pattern Recogni-tion Letters, Vol. 2, pp. 311-317.

Rosenfeld, A. (1985): Distance between fuzzy sets, Pattern Recognition Letters, Vol. 3, pp. 229-233.

Rosenfeld, A. (1990): Fuzzy rectangles, Pattern Recognition Letters, Vol. 11, pp. 677-679.

Rosenfeld, A., Janos, L. (1982): Some results on fuzzy digital convexity, Pattern Recognition, Vol. 15, pp. 379-382.

Rosenfeld, A., Kak, A. C. (1982): Digital Picture Processing, Vol. I/II, Academic Press, Inc.

Rosenfeld, A., Haber, S. (1985): The Perimeter of a fuzzy set, Pattern Recogni-tion, Vol. 18, pp. 125-130.

Rosenfeld, A., Pal, S. K. (1988): Image enhancement and thresholding by optimi-zation of fuzzy compactness, Pattern Recognition Letters, Vol. 7, pp. 77-86.

Rosenfeld, A., Pal, S. K. (1991): A fuzzy medial axis transformation based on fuzzy disks, Pattern Recognition Letters, Vol. 12, pp. 585-590.

Rosenfeld, A., Chaudhuri, B. B. (1996): On a metric distance between fuzzy sets. In: Pattern Recognition Letters, Vol. 17, pp. 1157-1160.

Pal, S. K., Ghosh, A. (1990): Index of area coverage of fuzzy image subsets and object extraction, Pattern Recognition Letters, Vol. 11, pp. 831-841.

Pal, S. K., Ghosh, A. (1992): Fuzzy Geometry in Image Analysis. In: Fuzzy Sets and Systems 48, North Holland, pp. 23-40.

On Fuzzy Clustering

Krishnapuram, R. (1993): Fuzzy Clustering Methods in Computer Vision. In: Proceedings von EUFIT’93, Vol. 2, pp. 720-730.

Krishnapuram, R. (1994): Generation of Membership Functions via Possibilistic Clustering, FUZZ-IEEE’94, pp. 902-908.

Krishnapuram, R., Keller, J. M. (1992): Fuzzy Set Theoretic Approach to Computer Vision: An Overview. In: IEEE International Conference on Fuzzy Systems, San Diego, pp. 135-142.

Krishnapuram, R., Keller, J. M. (1993): A possibilistic Approach to Clustering, IEEE Trans. Fuzzy Systems, Vol. 1, No. 2, pp. 98-110.

Krishnapuram, R., Keller, J. K. (1996): The Possibilistic C-Means Algorithm: Insights and Recommendations. In: IEEE Trans. Fuzzy

Systems, Vol. 4, No. 3, pp. 385-393.

Krishnapuram, R., Nasraoui, O., Frigui, H. (1992): The fuzzy C spherical shells algorithms: A new approach. In: IEEE Transactions on Neural Networks, Vol. 3, No. 5, pp. 663-671.

Bezdek, J. C. (1980): A Convergence Theorem for the Fuzzy ISODATA Cluster-ing Algorithms. In: IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI-2, No. 1, pp. 1-8.

Bezdek, J. C. (1981): Pattern Recognition with Fuzzy Objective Function Algo-rithms, Plenum Press, New York.

Dave, R. N. (1989): Use of the adaptive fuzzy clustering algorithm to detect lines in digital images. In: Intelligent Robots and Computer Vision VIII, Vol. 1192, No. 2, pp. 600-611.

Dave, R. N. (1992a): Boundary Detection through Fuzzy Clustering. In: Proceed-ings von IEEE International Conference on Fuzzy Systems, San Diego, pp. 127-134.

Dave, R. N. (1992b): Generalized fuzzy c-shells clustering and detection of circu-lar and elliptical boundaries. In: Pattern Recognition, Vol. 25, No. 7.

On Fuzzy Morphology

De Baets, B., Kerre, E., Gupta, M. (1995): The Fundamentals of Fuzzy Mathematical Morphology: Part 1&2. In: International Journal General Systems, vol. 23, pp. 155-171 (part 1), vol. 23, pp. 307-322 (part 2). 

De Baets, B. (1995): Idempotent closing and opening operations in fuzzy mathematical morphology. In: Proc. The Joint Int. Symp. on Uncertainty and Analysis and Annual Conf. of the North American Fuzzy Information Processing Society, USA, September 17-20, pp. 228-233.

De Baets, B. (1997): Fuzzy morphology: a logical approach. In: Ayyub A. and Gupta M. (eds.), Uncertainty Analysis in Engineering and Sciences, Kluwer Academic Publishers, 1997, pp. 53-67.

De Baets, B., Kwasnikowska, N., Kerre E. (1997): Fuzzy morphology based on conjunctive uninorms. In: Proc. 7th Inter. Fuzzy Systems Association Congress, Cze Republic, June 25-29, 1997, vol.1, pp. 215-220.

Di Gesu, V. (1988): Mathematical Morphology and Image Analysis: A fuzzy approach. In: Proceedings von Workshop on Knowledge-Based Systems and Models of Logical Reasoning, Ägypten.

Di Gesu, V., Maccarone, M. C., Tripiciano, M. (1991): MMFUZZY Mathematical morphology based on fuzzy operators. In: Proceedings von 4th IFSA Congress, pp. 29-32.

Di Gesu, V., Maccarone, M. C., Tripiciano, M. (1993): Mathematical Morphology based on fuzzy operators. In: Lowen, R., Roubens, M., Fuzzy Logic: State of the Art, Kluwer Academic Publisher, pp. 477-486.

Bloch, I., Maitre, H. (1993a): Constructing a fuzzy mathematical morphology: alternative ways. In: Proceedings von 2nd IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’93), pp.1303-1308.

Bloch, I., Maitre, H. (1993b): Mathematical morphology on fuzzy sets. In: Inter-national Workshop on Mathematical Morphology and its Applications to Signal Processing, Barcelona, pp. 151-156.

Bloch, I., Maitre, H. (1994): Fuzzy Mathematical Morphology. In: Ann.Math. Art. Intell., Vol. 10, pp. 55-84.

Bloch, I., Maitre, H. (1995): Fuzzy Mathematical Morphologies: A comparative study. In: Pattern Recognition, Vol. 28, No. 9, pp. 1341-1387.

Bloch, I., Pellot, C., Sureda, F., Herment, A (1996): Fuzzy Modelling and Fuzzy Mathematical Morphology applied to 3D Reconstruction of Blood Vessels by Multi-Modality Data Fusion. In: Yager, R., Dubois, D., Prade, H., Fuzzy Set Methods in Information Engineering: A Guided Tour of Applications, John Wiley & Sons, pp. 93-110, 1996.

Gasteratos A., Andreadis I., Tsalides Ph. (1998): Fuzzy Soft Mathematical Morphology, IEE Proceedings Vision Image and Signal Processing, 145, (1), 40-49, February 1998

Maccarone, M. C. (1996): Fuzzy Mathematical Morphology: Concepts and Appli-cations. In: Bijaoui, A., Vision Modeling and Information Coding, Vistas in Astronomy, Special issue, Vol. 40, Teil 4, pp. 469-477.

Sinha, D., Dougherty, E. R. (1992): Fuzzy Mathematical Morphology. In: Journal of Visual Communication and Image Representation, Vol. 3, No. 3, pp. 286-302.

On Fuzzy Measures/Integrals

Sugeno, M. (1974): Theory of Fuzzy Integrals and its Applications, Dissertation, Tokyo Institute of Technology, Japan.

Sugeno, M. (1977): Fuzzy Measures and Fuzzy Integrals: A Survey. In: Fuzzy Automata and Decision Processes, North Holland, Amsterdam, pp. 89-102.

Keller, J. M., Qiu, H., Tahani, H. (1986): The Fuzzy Integral in Image Segmenta-tion, Proceeding NAFIPS-86, pp. 324-338.

Keller, J. M., Gader, P., Tahani, H., Chiang, J. H., Mohamed, M. (1994): Ad-vances in fuzzy integration for pattern recognition. In: Fuzzy Sets and Systems, Vol. 65, pp. 273-283.

Pham, T. D., Yan, H. (1996): Color Image Segmentation- A Fuzzy-Integral Mountain-Clustering Approach, In: Image Segmentation Workshop 1996, The Australian Pattern Recognition Society, Sydney, pp. 27-32.

Grabisch, M., Murofushi, T., Sugeno, M. (1992): Fuzzy measure of fuzzy events defined by fuzzy integrals. In: Fuzzy Sets and Systems, Vol. 50, pp. 293-313.

Grabisch, M., Sugeno, M. (1992): Multi-attribute classification using fuzzy inte-gral. In: IEEE Conf. Fuzzy Systems, San Diego, pp. 47-54.

Grabisch, M., Nicolas, J. M. (1994): Classification by fuzzy integral: Performance and tests. In: Fuzzy Sets and Systems, Vol. 65, pp. 255-271.

On Fuzzy Image Enhancement

Craig, M., Schneider, M. (1992): On the use of fuzzy sets in histogram equaliza-tion. In: Fuzzy Sets and Systems, North Holland, Vol. 45, pp. 271-278.

Pal, S. K., King, R. A. (1981a): Histogram equalization with S and Pi functions in detecting X-ray edges. In: Electronics Letters, Vol. 17, No. 8, pp. 302-304.

Pal, S. K., King, R. A. (1981b): Image Enhancement Using Smoothing with Fuzzy Sets. In: IEEE Trans. Syst., Man, Cybern., Vol. SMC-11, No. 7., pp. 494-501.

Tizhoosh, H. R., Fochem, M. (1995): Image Enhancement with Fuzzy Histogram Hyperbolization. In: Proceedings von EUFIT’95, Vol. 3, pp. 1695-1698.

Tizhoosh, H. R., Krell, G., Michaelis, B. (1997a): Locally Adaptive Fuzzy Image Enhancement. In: Reusch, B., Computational Intelligence, Springer-Verlag, pp. 272-276.

Tizhoosh, H. R., Krell, G., Michaelis, B. (1997b): On Fuzzy Image Enhancement of Megavoltage Images in Radiation Therapy. In: 6th IEEE International Conference on Fuzzy Systems, Barcelona, Spanien.

On Fuzzy Perceptual Grouping

alker, E. L., Kang, H.-B. (1992): Perceptual Grouping Based on Fuzzy Sets. In: IEEE International Conference on Fuzzy Systems, San Diego, Vol. 1, pp. 651-659.

Walker, E. L., Kang, H.-B. (1994): Fuzzy Measures of Uncertainty in Perceptual Grouping. In: Proceedings von 3th IEEE International Conference on Fuzzy Systems, Vol. 3, pp. 2020-2024.

On Measures of Fuzziness/Image Information

Bhandari, D., Pal, N. R., Majumder, D. D. (1992a): Fuzzy Divergence: A new measure for image segmentation. In: Proceedings von 2nd International Confer-ence on Fuzzy Logic & Neural Networks, Iizuka, Japan, pp. 645-648.

Bhandari, D., Pal, N. R., Majumder, D. D. (1992b): Fuzzy Divergence, probability measure of fuzzy events and image thresholding. In: Pattern Recognition Let-ters, Vol. 13, pp. 857-867.

De Luca, A., Termini, S. (1972): A definition of a nonprobabilistic entropy in the setting of fuzzy set theory, Information and Control, Vol. 20, pp. 301-312.

Kandel, A., Friedman, M., Schneider, M. (1989): The use of weighted fuzzy ex-pected value (WFEV) in fuzzy expert systems. In: Fuzzy Sets and systems, Vol. 31, pp. 37-45.

Pal, S. K. (1992a): Fuzziness, Image Information and Scene Analysis. In: Yager, R., Zadeh, L.A., An Introduction to Fuzzy Logic Applications in Intelligent Systems, Kluwer Academic Publishers, pp. 147-184.

Pal, S. K. (1994): Fuzzy Sets in Image Processing and Recognition. In: Marks, R. J., Fuzzy Logic Technology and Applications, USA , pp.33-40.

Pal, S. K., Pal, N. K. (1991): Entropy: a new definition and its applications, IEEE Trans. Syst. Man and Cybernetics, Vol. SMC-21, No. 5.

Pal, S. K., Pal, N. K. (1992): Higher order fuzzy entropy and hybrid entropy of a set, Information Science, Vol. 61, No. 3, pp. 211-231.

See also the Rosendfeld Vision Bibliography 1984-1998 (USA)
or see directly the results for keywords fuzz, fuzziness, fuzzy