This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Automatic Construction of Structural Models Incorporating Discontinuous Transformations
April 1996 (vol. 18 no. 4)
pp. 400-411

Abstract—We present an approach to automatic construction of structural models incorporating discontinuous transformations, with emphasis on application to unconstrained handwritten character recognition. We consider this problem as constructing inductively, from the data set, some shape descriptions that tolerate certain types of shape transformations. The approach is based on the exploration of complete, systematic, high-level models on the effects of the transformations, and the generalization process is controlled and supported by the high-level transformation models. An analysis of the a priori effects of commonly occurring discontinuous transformations is carried out completely and systematically, leading to a small, tractable number of distinct cases. Based on this analysis, an algorithm for the inference of super-classes under these transformations is designed. Furthermore, through examples and experiments, we show that the proposed algorithm can generalize unconstrained handwritten characters into a small number of classes, and that one class can represent various deformed patterns.

[1] H.S. Baird, "Feature Extraction for Hybrid Structural/Statistical Pattern Classification," Computer Vision, Graphics, and Image Processing, vol. 42, pp. 318-333, 1988.
[2] J. Camillerap, G. Lorette, G. Menier, H. Oulhadj, and J.C. Pettier, "Off-Line and On-Line Methods for Cursive Handwriting Recognition," From Pixels to Features: Frontiers in Handwriting Recognition, S. Impedovo and J.-C. Simon, eds., pp. 273-287.Amsterdam: Elsevier, 1992.
[3] R.T. Chin and C.R. Dyer, "Model-Based Recognition in Robotics Vision," ACM Computing Surveys, vol. 18, pp. 67-108, Mar. 1986.
[4] M.B. Clowes, "On Seeing Things," Artificial Intelligence, vol. 2, pp. 79-116, 1971.
[5] J.H. Connell and M. Brady, "Generating and Generalizing Models of Visual Objects," Artificial Intelligence, vol. 31, pp. 159-183, 1987.
[6] T.G. Dietterich and R.S. Michalski, "A Comparative Review of Selected Models for Learning from Examples," Machine Learning, R.S. Michalski, J.G. Carbonell, and T.M. Mitchell, eds. Los Altos, Calif.: Morgan Kaufmann, 1983.
[7] R.M. Haralick and L.G. Shapiro, "The Consistent Labeling Problem: Part 1," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 1, pp. 173-184, 1979.
[8] D.A. Huffman, "Impossible Objects as Nonsense Sentences," Machine Intelligence, B. Meltzer and D. Michie, eds., vol. 6, pp. 295-323.Edinburgh: Edinburgh Univ. Press, 1971.
[9] L. Lam and C.Y. Suen, "Structural Classification and Relaxation Matching of Totally Unconstrained Handwritten Zip-Code Numbers," Pattern Recognition, vol. 21, no. 1, pp. 19-31, 1988.
[10] S. Mori, C.Y. Suen, and K. Yamamoto, “Historical Review of OCR Research and Development,” Proc. IEEE, vol. 80, no. 7, pp. 1,029-1,058, 1992.
[11] H. Nishida, "Model-Based Shape Matching with Structural Feature Grouping," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 3, pp. 315-320, 1995.
[12] H. Nishida, "Structural Feature Extraction Using Multiple Bases," Computer Vision and Image Understanding, vol. 62, no. 1, pp. 78-89, 1995.
[13] H. Nishida, "Curve Description Based on Directional Features and Quasi-Convexity/Concavity," Pattern Recognition, vol. 28, no. 7, pp. 1,045-1,051, 1995.
[14] H. Nishida, "A Structural Model of Shape Deformation," Pattern Recognition, vol. 28, no. 10, pp. 1,611-1,620, 1995.
[15] H. Nishida, “An Approach to Integration of Off-Line and On-line Recognition of Handwriting,” Pattern Recognition Letters, vol. 16, no. 11, pp. 1,213-1,219, Nov. 1995.
[16] H. Nishida, "Shape Recognition by Integrating Structural Descriptions and Geometrical/Statistical Transforms," Computer Vision and Image Understanding, in press.
[17] H. Nishida, "A Structural Model of Curve Deformation by Discontinuous Transformations," Graphical Models and Image Processing, vol. 58, no. 2, 1996.
[18] H. Nishida and S. Mori, "Algebraic Description of Curve Structure," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 5, pp. 516-533, May 1992.
[19] H. Nishida and S. Mori, "An Algebraic Approach to Automatic Construction of Structural Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 12, pp. 1,298-1,311, Dec. 1993.
[20] T. Pavlidis, Structural Pattern Recognition.New York: Springer-Verlag, 1977.
[21] T. Poston and I. Stewart, Catastrophe Theory and Its Applications.London: Pitman Publishing, 1978.
[22] J. Rocha and T. Pavlidis, "A Shape Analysis Model With Applications to a Character Recognition System," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, pp. 393-404, 1994.
[23] W.B. Seales and O.D. Faugeras, "Building Three-Dimensional Object Models from Image Sequences," Computer Vision and Image Understanding, vol. 61, no. 3, pp. 308-324, 1995.
[24] K. Sengupta and K.L. Boyer, “Organizing Large Structural Modelbases,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 4, pp. 321-332, Apr. 1995.
[25] L.G. Shapiro and R.M. Haralick, "Structural Descriptions and Inexact Matching," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 3, no. 5, pp. 504-519, May 1981.
[26] L.G. Shapiro and R.M. Haralick, "Organization of Relational Models for Scene Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 4, no. 11, pp. 595-602, Nov. 1982.
[27] T. Suzuki and S. Mori, "Structural Description of Line Images by the Cross Section Sequence Graph," Int'l J. Pattern Recognition and Artificial Intelligence, vol. 7, no. 5, pp. 1,055-1,076, 1993.
[28] R. Thom, StabilitéStructurelle et Morphogénèse.Paris: InterEditions, 1977.
[29] N. Ueda and S. Suzuki, "Learning Visual Models from Shape Contours Using Multiscale Convex/Concave Structure Matching," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 4, pp. 337-352, Apr. 1995.
[30] T. Wakahara, H. Murase, and K. Odaka, “On-Line Handwriting Recognition,” Proc. IEEE, vol. 80, no. 7, pp. 1,181-1,194, 1992.
[31] P.H. Winston, "Learning Structural Descriptions from Examples," The Psychology of Computer Vision, P.H. Winston, ed., chap. 5. New York: McGraw Hill, 1975.
[32] P.H. Winston, "Learning and Reasoning by Analogy," Comm. ACM, vol. 23, pp. 689-703, 1980,
[33] K. Yamamoto and A. Rosenfeld, "Recognition of Hand-Printed Kanji Character by a Relaxation," Proc. Sixth Int'l Conf. Pattern Recognition, pp. 395-398,Munich, 1982.
[34] K. Yamamoto and S. Mori, "Recognition of Handprinted Characters by Outermost Point Method," Pattern Recognition, vol. 12, pp. 229-236, 1980.
[35] X. Yuan, "A Mechanism of Automatic 3D Object Modeling," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 3, pp. 307-311, Mar. 1995.
[36] S. Zhang, G.D. Sullivan, and K.D. Baker, "The Automatic Construction of a View-Independent Relational Model for 3-D Object Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 6, pp. 531-544, June 1993.

Index Terms:
Character recognition, handwriting recognition, learning, shape analysis, shape transformation, structural model.
Citation:
Hirobumi Nishida, "Automatic Construction of Structural Models Incorporating Discontinuous Transformations," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 4, pp. 400-411, April 1996, doi:10.1109/34.491621
Usage of this product signifies your acceptance of the Terms of Use.