Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMM
نویسندگان
چکیده
A holistic system for the recognition of handwritten Farsi/Arabic words using right}left discrete hidden Markov models (HMM) and Kohonen self-organizing vector quantization 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 neighborhood information preserved in the self-organizing feature map (SOFM), is used for smoothing the observation probability distributions of trained HMMs. Experiments carried out on test samples show promising performance results. ( 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
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ورودعنوان ژورنال:
- Pattern Recognition
دوره 34 شماره
صفحات -
تاریخ انتشار 2001