Bibliography Image Processing, Pattern Recognition & Neural Networks

 Books on Image Processing, Coding and Vision 

Kenneth R. Castleman, Digital Image Processing, Prentice-Hall 1996, 
ISBN(Cloth): 0-13-211467-4 
(Description and errata at: http://www.phoenix.net/~castlman").

Fractal Image Encoding and Analysis: A NATO ASI Series Book, 
Yuval Fisher (Ed.), Springer Verlag, New York, 1996.

S.Z. Li, Markov Random Field, Modeling in Computer Vision, Springer-Verlag, 
ISBN 0-387-70145-1, 1995.

G. Winkler, Image Analysis: Markov Fields and Dynamic Monte Carlo Methods,
Springer-Verlag, New York, 1995, ISBN 0-387-57069-1.

Fractal Image Compression: Theory and Application, Yuval Fisher (Ed.), 
Springer Verlag, New York, 1995.

T. Lindeberg, Scale-space theory in computer vision, 
Kluwer Academic Publishers, ISBN 0-7923-9418-6, 1994.

Masters, T. , Signal and Image Processing with Neural Networks: 
A C++ Sourcebook, NY: Wiley, 1994.

Henk J.A.M. Heijmans, Morphological Image Operators,
Academic Press, Boston, ISBN 0-12-014599-5, 1994.

Mathematical Morphology and its Applications to Image Processing, J.Serra and 
P.Soille editors, Computational Imaging and Vision, Kluwer Academic 
Publishers, Dordrecht, 1994.

V.S. Nalwa, A Guided Tour of Computer Vision, Addision-Wesley, 1993.

I. Pitas, Digital Image Processing Algorithms, Prentice-Hall, 
Englewood Cliffs, 1993.

Markov Random Fields: Theory and Applications, 
Chellappa R. and Jain, A. editors, Academic Press, 1993.

Michael F. Barnsley and Lyman P. Hurd, Fractal Image Compression, AK Peters, 
Ltd, 1993, ISBN 1-56881-000-8.

Rafael C. Gonzalez and Richard E. Woods, Digital Imaging Processing,
Addison-Wesley, Reading, Massachusetts, USA, 1992.

R.M. Haralick and L.G. Shapiro, Computer and Robot Vision, volume I,
Addison-Wesley, Reading, 1992.

R.M. Haralick and L.G. Shapiro, Computer and Robot Vision, volume II,
Addison-Wesley, Reading, 1993.

J.C. Russ, The Image Processing Handbook, CRC Press, Inc., Boca Raton, Ann
Arbor, London, Tokyo, 1992, ISBN 0-8493-4233-3.

D. Vernon, Machine vision - Automated Visual Inspection And Robot Vision,
Prentice Hall, New York, 1991.

William K. Pratt, Digital Image Processing (second edition), John Wiley & Sons, 
New York, 1991, ISBN 0-471-85766-1.

George Wolberg, Digital Image Warping, IEEE Computer Society Press Monograph, 
1990, ISBN 0-8186-8944-7.

L.J. Galbiati, Jr, Machine Vision and Digital Image Processing Fundamentals,
Prentice-Hall International, Inc, Englewood Cliffs, 1990.

M. Ejiri, Machine Vision - A Practical Technology for Advanced Image
Processing, Gordon and Breach Science Publishers, New York, 1989.

J.C. Simon, From Pixels to Features, North Holland, Amsterdam, 1989.

Jan Teubner, Digital Image Processing, Prentice Hall, Copenhagen, 1989.

Anil K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 
Englewood Cliffs, 1989, ISBN 0-13-336165-9.

B.K.P. Horn, Robot Vision, MIT Press, Cambridge, 1987.

M.J.B. Duff and T.J. Fountain, Cellular Logic Image Processing, Academic Press,
London, 1986.

John C. Russ, Practical Stereology, Plenum Press, New York, 1986.

D.E. Dudgeon and R.M. Mersereau, Multidimensional Digital Signal Processing,
Prentice-Hall, Inc, Englewood Cliffs, 1984.

R.W. Hamming, Digital Filters, Prentice-Hall, Englewood Cliffs, NJ, 1983.

A. Rosenfeld and A.C. Kak, Digital Picture Processing, volume 1, Academic
Press, Orlando, 1982.

A. Rosenfeld and A.C. Kak, Digital Picture Processing, volume 2, Academic
Press, Orlando, 1982.

J. Serra, Image Analysis and Mathematical Morphology, Academic Press, London,
1982.

D.H. Ballard and C.M. Brown, Computer vision, Prentice-Hall, Englewood Cliffs,
1982.

D. Marr, Vision, W.H. Freeman and Company, San Fransisco, 1982.

T. Pavlidis, Graphics and Image Processing, Computer Science Press, 1982.

A.V. Oppenheim, R.W. Schafer, Digital Signal Processing, Prentice-Hall, 1975.



 Books on Pattern Recognition 

V.N. Vapnik, The Nature of Statistical Learning Theory, Springer,1996.
                                       
Ripley, B.D. (1996) Pattern Recognition and Neural Networks, Cambridge:
Cambridge University Press, ISBN 0-521-46086-7 (hardback), xii+403 pages, 1996.

Bishop, C.M. (1995). Neural Networks for Pattern Recognition, Oxford:
Oxford University Press. ISBN 0-19-853849-9 (hardback) or 0-19-853864-2
(paperback), xvii+482 pages, 1995.

D. Paulus and J. Hornegger, Pattern Recognition and Image Processing in C++,
Vieweg, Braunschweig, 1995.

Albert Nigrin, Neural Networks for Pattern Recognition, 1993, A Bradford Book,
ISBN 0-262-14054-3.

J.R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers,
San Mateo, California, 1993.

Robert Schalkhoff, Pattern Recognition, statistical, structural and neural
approaches, John Wiley and Sons, New York, 1992.

G.J. McLachlan, Discriminant Analysis and Statistical Pattern Recognition, John
Wiley and Sons, New York, 1992.

Weiss, S.M. & Kulikowski, C.A. , Computer Systems That Learn,
Morgan Kaufmann., San Mateo, California, ISBN 1 55860 065 5., 1991

K. Fukunaga, Introduction to Statistical Pattern Recognition (Second Edition),
Academic Press, New York, 1990.

Y.H. Pao, Adaptive Pattern Recognition and Neural Networks, Addison Wesley,
Reading, Massachusetts, 1989.

Judea Pearl, Probabilistic Reasoning in Intelligent Systems, Morgan Kaufmann, 
1988, ISBN 0-934613-73-7.

Satoshi Watanabe, Pattern Recognition, Human and Mechanical, John Wiley & Sons,
New York, 1985.

T.Y. Young and K.S. Fu, Handbook of Pattern Recognition and Image Processing,
Academic Press, Orlando, Florida, 1986, ISBN 0127745602.
(A second volume edited by Dr. Young was published in 1994, ISBN 0127745610.)

L. Breiman, J.H. Friedman, R.A. Olshen, and C.J. Stone, Classification and
regression trees, Wadsworth, California, 1984.

P.A. Devijver and J. Kittler, Pattern Recognition, a Statistical Approach,
Prentice Hall, Englewood Cliffs, London, 1982.

R.C. Gonzalez and M.G. Thomason, Syntactic pattern recognition - An
introduction, Addison-Wesley, Reading, 1982.

J. Sklanski and G.N. Wassel, Pattern Classifiers and Trainable Machines,
Springer, New York, 1981.

. R.O. Duda and P.E. Hart, Pattern classification and scene analysis, John
Wiley & Sons, New York, 1973.
(A second edition is being prepared by David Stork)



 Books on Neural Networks 

T. Kohonen, Self-Organizing Maps, Springer, Berlin, 1995.

LiMin Fu, Neural Networks in Computer Intelligence, McGraw-Hill, Inc., New
York, NY, 1994.

S. Haykin, Neural Networks, A Comprehensive Foundation, Macmillan, New York,
NY, 1994.

Masters, Timothy, Practical Neural Network Recipes in C++, Academic Press, 
ISBN 0-12-479040-2, US $45 incl. disks, 1994

Fausett, L. V., Fundamentals of Neural Networks: Architectures,
Algorithms and Applications, Prentice Hall, ISBN 0-13-334186-0. Also
published as a Prentice Hall International Edition, ISBN 0-13-042250-9., 1994

S.Y. Kung, Digital Neural Networks, Prentice Hall, Englewood Cliffs, NJ, 1993.

Stephen I. Gallant, Neural Network Learning and Expert systems, Massachusetts
Inst. of Technology, Cambridge, Massachusetts, 1993.

Cichocki, A. and Unbehauen, R. Neural Networks for Optimization
and Signal Processing. NY: John Wiley & Sons, ISBN 0-471-930105 (hardbound),
526 pages, 1993.

Smith, M., Neural Networks for Statistical Modeling, NY: Van Nostrand
Reinhold, 1993.

J.M. Zurada, Artificial Neural Systems, West Publishing, St. Paul, MN, 1992.

B. Kosko, Neural Networks and Fuzzy Systems, Prentice-Hall, 1992,
ISBN 0-13-611435-0.

J. C. Bezdek and S. K. Pal, Fuzzy Models for Pattern Recognition, 
eds. IEEE Press, 1992.

Hertz, John, Krogh, Anders, and Palmer, Richard, Introduction to the Theory of
Neural Computation. Addison-Wesley: Redwood City, California. ISBN
0-201-50395-6 (hardbound) and 0-201-51560-1 (paperbound), 1991.

Freeman, J.A. and Skapura, D.M., Neural Networks: Algorithms,
Applications, and Programming Techniques, Reading, MA: Addison-Wesley, 1991.

B. Muller and J. Reinhardt, Neural networks, an introduction, Springer-Verlag,
Berlin, 1991.

Aleksander, I. and Morton, H., An Introduction to Neural Computing.
Chapman and Hall. (ISBN 0-412-37780-2)., 1990.

Dayhoff, J. E., Neural Network Architectures: An Introduction. Van
Nostrand Reinhold: New York., 1990

Beale, R. and Jackson, T., Neural Computing, an Introduction. Adam
Hilger, IOP Publishing Ltd : Bristol. (ISBN 0-85274-262-2)., 1990.

P.D. Wasserman, Neural Computing, theory and practice, Van Nostrand Reinhold,
New York, 1989.

I. Aleksander, Neural Computing Architectures, North Oxford Academic, London,
1989.

T. Kohonen, Self-Organization and Associative Memory, Springer-Verlag, 1989.

S. Grossberg, The Adaptive Brain I: Cognition, Learning, Reinforcement, and
Rythm, Elsevier/North Holland, Amsterdam, 1987.

S. Grossberg, The Adaptive Brain II: Vision, Speech, Language and Motor
Control, Elsevier/North Holland, Amsterdam, 1987.



 Books of Historical Interest 

K. Fukunaga, Introduction to Statistical Pattern
Recognition (First Edition), Academic Press, New York, 1972.

J.M. Mendel and K.S. Fu, Adaptive, learning, and pattern recognition systems:
theory and applications, Academic Press, New York, 1970.

M. Minsky and S. Papert, Perceptrons: An Introduction to Computational
Geometry, MIT Press, Cambridge, Mass, 1969.

A.G. Arkadev and E.M. Braverman, Teaching Computers to Recognize Patterns,
Academic Press, London, 1966.

Nilsson, N.J., Learning Machines, McGraw-Hill, New York, 1965.

G.S. Sebestyen, Decision-Making Processes in Pattern Recognition, Macmillan,
New York, 1962.

Rosenblatt, F., Principles of Neurodynamics: Perceptrons and the theory of
brain mechanisms, Spartan Books, Washington, D.C., 1962.

Last modified: Wednesday, June 25, 1997