Features Modelling in Discrete and Continuous Hidden Markov Models for Handwritten Arabic Words Recognition

Benzenache Amine; Seridi Hamid; Akdag Herman

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Features Modelling in Discrete and Continuous Hidden Markov Models for Handwritten Arabic Words Recognition

机译：离散和连续隐马尔可夫模型中的特征建模用于手写阿拉伯语单词识别

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摘要

The arab writing is originally cursive, difficult to segment and has a great variability. To overcome these problems, we propose two holistic approaches for the recognition of the handwritten arabic words in a limited vocabulary based on the Hidden Markov Models (HMMs): discrete with wk-means and continuous. In the suggested approach, each word of the lexicon is modelled by a discrete or continuous HMM. After a series of pre-processing, the word image is segmented from right to left in succession frames of fixed or variable size in order to generate a sequence vector of statistical and structural parameters which will be submitted to two classifiers to identify the word. To illustrate the efficiency of the proposed systems, significant experiments are carried out on IFN/ENIT benchmark database.

机译：阿拉伯文字原本是草书，难以分割，并且变化很大。为了克服这些问题，我们提出了两种基于隐马尔可夫模型（HMM）的整体方法来识别有限词汇中的手写阿拉伯语：wk-means离散和连续。在建议的方法中，词典的每个单词都由离散或连续的HMM建模。经过一系列的预处理后，单词图像将按固定大小或可变大小的连续帧从右到左进行分割，以生成统计和结构参数的序列向量，并将其提交给两个分类器以识别单词。为了说明所提出系统的效率，在IFN / ENIT基准数据库上进行了重要的实验。

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来源
《The international arab journal of information technology》 |2017年第5期|681-690|共10页
作者
Benzenache Amine; Seridi Hamid; Akdag Herman;
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作者单位

Univ 8 Mai 1945 Guelma, Lab Sci & Informat Technol & Commun, Guelma, Algeria;

Univ 8 Mai 1945 Guelma, Lab Sci & Informat Technol & Commun, Guelma, Algeria;

Univ Paris 08, Lab Informat Avancee St Denis, Paris, France;

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正文语种 eng
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Recognition of the handwritten arabic words; holistic approach; DHMMs; CHMMs; k-means; wk-means; algorithm of Viterbi; modified EM algorithm;

机译：手写阿拉伯语单词识别;整体方法;DHMM;CHMM;k均值;wk均值;维特比算法;改进的EM算法;

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专利

1. Effective technique for the recognition of offline Arabic handwritten words using hidden Markov models [J] . Sherif Abdel Azeem, Hany Ahmed International Journal on Document Analysis and Recognition (IJDAR) . 2013,第4期

机译：使用隐马尔可夫模型识别离线阿拉伯语手写单词的有效技术
2. Effective technique for the recognition of offline Arabic handwritten words using hidden Markov models [J] . Sherif Abdel Azeem, Hany Ahmed International Journal on Document Analysis and Recognition . 2013,第4期

机译：使用隐马尔可夫模型识别离线阿拉伯语手写单词的有效技术
3. Off-line recognition of handwritten Arabic words using multiple hidden Markov models [J] . Somaya Almaadeed, Colin Higgins, Dave Elliman Knowledge-Based Systems . 2004,第2a4期

机译：使用多个隐马尔可夫模型离线识别手写阿拉伯语单词
4. Offline handwritten Arabic words recognition using Zernike moments and Hidden Markov Models [C] . El-Feghi I., Elmahjoub F., Alswady B., 2010 International Conference on Computer Applications and Industrial Electronics . 2010

机译：使用Zernike矩和隐马尔可夫模型的离线手写阿拉伯语单词识别
5. A discrete hidden Markov model for the recognition of handwritten Farsi words [D] . Jifroodian-Haghighi, Puntis. 2010

机译：用于识别波斯波斯文字的离散隐马尔可夫模型
6. Assessment of Dysarthria Using One-Word Speech Recognition with Hidden Markov Models [O] . Seung Hak Lee, Minje Kim, Han Gil Seo, 2019

机译：使用隐马尔可夫模型的单字语音识别评估构音障碍
7. Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition [O] . Alkhateeb, JH, Pauplin, O, Ren, J, 2011

机译：隐马尔可夫模型和动态贝叶斯网络分类器在手写阿拉伯文字识别中的性能

Features Modelling in Discrete and Continuous Hidden Markov Models for Handwritten Arabic Words Recognition

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