Fuzzy algorithm for contextual character recognition

Measuring the likeness between data in different ways is an important part of pattern recognition and, over the years, many such measures have been developed. This paper proposes an asymmetric measure of likeness based on the concept of context dependent divergence. This is used to construct a numerical descriptor for images and, in conjunction with fuzzy sets, to develop a supervised learning algorithm. When applied to the problem of handwritten digit recognition, the algorithm produces promising and highly accurate results.

[1]  A. Ralescu,et al.  Context Based Modeling of Planar Shapes , 2022 .

[2]  Ashutosh Malaviya,et al.  Object recognition using fuzzy set theoretic techniques , 1993, Defense, Security, and Sensing.

[3]  Paramvir Bahl,et al.  Recognition of handwritten word: First and second order hidden Markov model based approach , 1989, Pattern Recognit..

[4]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Eric Lecolinet,et al.  A Survey of Methods and Strategies in Character Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Yi Lu,et al.  Character segmentation in handwritten words - An overview , 1996, Pattern Recognit..

[7]  Azriel Rosenfeld,et al.  The fuzzy geometry of image subsets , 1984, Pattern Recognit. Lett..

[8]  Pepe Siy,et al.  Fuzzy logic for handwritten character recognition , 1973 .

[9]  Jonathan Lawry,et al.  A mass assignment theory of the probability of fuzzy events , 1996, Fuzzy Sets Syst..

[10]  Isabelle Bloch,et al.  On fuzzy distances and their use in image processing under imprecision , 1999, Pattern Recognit..

[11]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[12]  James G. Shanahan.  Soft Computing for Knowledge Discovery , 2000 .

[13]  Sung Yang Bang,et al.  A variation measure for handwritten character image data using entropy difference , 1997, Pattern Recognit..

[14]  Keiji Yamada,et al.  A stochastic model for handwritten word recognition using context dependency between character patterns , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[15]  Gösta H. Granlund,et al.  Fourier Preprocessing for Hand Print Character Recognition , 1972, IEEE Transactions on Computers.

[16]  Sankar K. Pal,et al.  Fuzzy models for pattern recognition : methods that search for structures in data , 1992 .

[17]  Karl Sims,et al.  Handwritten Character Classification Using Nearest Neighbor in Large Databases , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  B. Martins.  Recognition of isolated handprinted characters , 1996, 1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929).

[19]  Azriel Rosenfeld,et al.  Fuzzy Digital Topology , 1979, Inf. Control..

[20]  Waibhav Tembe.  PATTERN EXTRACTION USING A CONTEXT DEPENDENT MEASURE OF DIVERGENCE AND ITS VALIDATION , 2001 .

[21]  Roberto Guerrieri,et al.  A novel metric for nearest-neighbor classification of hand-written digits , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.

[22]  Isabelle Bloch,et al.  Directional relative position between objects in image processing: a comparison between fuzzy approaches , 2003, Pattern Recognit..

[23]  Paul D. Gader,et al.  Automatic Feature Generation for Handwritten Digit Recognition , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Nei Kato,et al.  A Handwritten Character Recognition System Using Directional Element Feature and Asymmetric Mahalanobis Distance , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Adam Krzyżak,et al.  Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..

[26]  James F. Baldwin,et al.  A Theory of Mass Assignments for Artificial Intelligence , 1991, Fuzzy Logic and Fuzzy Control.

[27]  P. Mahalanobis.  On the generalized distance in statistics , 1936 .