A shape-recognition model using dynamical links

A shape-recognition method is proposed, inspired from the dynamic-link theory of von der Malsburg (1981). The quality of a match between two images is assessed through an elastic cost functional; the minimal value reached by the cost over a suitably-defined space of maps is viewed as a distance between these two images. Experiments on nearest-neighbour classification of handwritten numerals are presented, using a computationally effective procedure for finding a reliable estimate of the matching distance.

[1]  Yann LeCun,et al.  Efficient Pattern Recognition Using a New Transformation Distance , 1992, NIPS.

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

[3]  Lawrence D. Jackel,et al.  Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.

[4]  Isabelle Guyon Réseaux de neurones pour la reconnaissance des formes : architectures et apprentissage , 1988 .

[5]  David J. Burr,et al.  Elastic Matching of Line Drawings , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  I. Biederman,et al.  Dynamic binding in a neural network for shape recognition. , 1992, Psychological review.

[7]  Joachim M. Buhmann,et al.  Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.

[8]  Ruzena Bajcsy,et al.  Multiresolution elastic matching , 1989, Comput. Vis. Graph. Image Process..

[9]  U. Grenander,et al.  Structural Image Restoration through Deformable Templates , 1991 .

[10]  Sargur N. Srihari,et al.  Off-Line Cursive Script Word Recognition , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  E Bienenstock,et al.  Elastic matching and pattern recognition in neural networks. , 1989 .

[12]  Azriel Rosenfeld,et al.  From volumes to views: An approach to 3-D object recognition , 1992, CVGIP Image Underst..

[13]  Elie Bienenstock,et al.  A neural network for invariant pattern recognition. , 1987 .

[14]  Charles C. Tappert,et al.  Cursive Script Recognition by Elastic Matching , 1982, IBM J. Res. Dev..

[15]  Ulf Grenander,et al.  Hands: A Pattern Theoretic Study of Biological Shapes , 1990 .

[16]  Geoffrey E. Hinton,et al.  Adaptive Elastic Models for Hand-Printed Character Recognition , 1991, NIPS.

[17]  Christoph von der Malsburg,et al.  The Correlation Theory of Brain Function , 1994 .

[18]  Elie Bienenstock,et al.  Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.

[19]  C. Malsburg,et al.  Statistical Coding and Short-Term Synaptic Plasticity: A Scheme for Knowledge Representation in the Brain , 1986 .

[20]  James A. Pittman,et al.  Recognizing Hand-Printed Letters and Digits Using Backpropagation Learning , 1991, Neural Computation.

[21]  C. von der Malsburg,et al.  Distortion invariant object recognition by matching hierarchically labeled graphs , 1989, International 1989 Joint Conference on Neural Networks.

[22]  James A. Pittman,et al.  Recognizing Hand-Printed Letters and Digits , 1989, NIPS.