Selective Feature-to-Feature Adhesion for Recognition of Cursive Handprinted Characters

Authors:
Cheng-Yuan Liou;Hsin-Chang Yang
Affiliations:
National Taiwan Univ., Taipei, Taiwan;National Taiwan Univ., Taipei, Taiwan
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1999

Citing 7
Cited 2

Self-organization and associative memory: 3rd edition

Self-organization and associative memory: 3rd edition
Hierarchical attributed graph representation and recognition of handwritten Chinese characters

Pattern Recognition
Original Contribution: Population coding by simultaneous activities of neurons in intrinsic coordinate systems defined by their receptive field weighting functions

Neural Networks
Original Contribution: Recognition and segmentation of connected characters with selective attention

Neural Networks
Handprinted Character Recognition Based on Spatial Topology Distance Measurement

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Shape Analysis Model with Applications to a Character Recognition System

IEEE Transactions on Pattern Analysis and Machine Intelligence
Character Recognition Without Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence

Neural Network Method for Protein Structure Search Using Cell-Cell Adhesion

Neural Information Processing
Backbone structure of hairy memory

ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I

Quantified Score

Hi-index	0.15

Visualization

Abstract

A structural-feature-to-structural-feature configuration is naturally constructed using a set of sampled features from a cursive pattern. These features are sampled by maximally fitting bended ellipses in local strokes. This configuration is transformed into an undirected graph to resolve the asymmetric difficulty. The compatibility associated with the graph is further formulated into a devised Hopfield network, where both interfeature and interlink similarities are incorporated into the compatibility. We operate this network to recognize a radical as a whole in a handprinted pattern to accomplish the selective attention task.