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Printed amazigh character recognition by a hybrid approach based on Hidden Markov Models and the Hough transform

机译:通过基于隐马尔可夫模型和Hough变换的混合方法印刷AmazIgh字符识别

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We present an automatic system for off-line printed Amazigh handwritten characters recognition, based on an hybrid approach combining Hidden Markov Models (HMM) and the Hough transform. After preprocessing on the image of the character, the representative chain of the character is build from the Hough Transformation. This chain is translated into sequence of observations that is used for the learning phase, by the HMM. Finally, we use the Forword classifier to recognize the character. The experimental results show the robustness of the system.
机译:我们提出了一种自动系统,用于基于混合方法组合隐马尔可夫模型(HMM)和Hugh变换的混合方法。在预处理角色的图像之后,角色的代表链是从霍夫变换构建的。该链被肝脏转化为用于学习阶段的观察序列。最后,我们使用forwword分类器来识别该字符。实验结果表明了系统的稳健性。

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