A Hybrid Handwritten Word Recognition Using Self-Organizing Feature Map, Discrete HMM, and Evolutionary Programming

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IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
Year:
2000

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Character Representation and Recognition Using Quadtree-based Fractal Encoding Scheme

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition

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Abstract

A hybrid system for the recognition of handwritten Farsi words using self-organizing feature map, right-left discrete hidden Markov models, and evolutionary programming is presented. The histogram of chain-code directions of the image strips, scanned from right to left by a sliding window, is used as feature vectors. The self-organizing feature map is used for constructing the codebook and smoothing the observation probability distributions. A population based approach using evolutionary programming with a self-adaptive Cauchy mutation operator is used to find an appropriate initial model as starting point for the classical Baum-Welch algorithm. Experimental results were found to be promising.