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A New Approach for Segmentation and Recognition of Arabic Handwritten Touching Numeral Pairs

机译:阿拉伯手写触摸数字对的分割与识别新方法

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摘要

In this paper, we propose a new approach on segmentation and recognition of off-line unconstrained Arabic handwritten numerals, which failed to be segmented with connected component analysis. In our approach, the touching numerals are automatically segmented when a set of parameters is chosen. Models with different sets of parameters for each numeral pair are designed for recognition. Each image in each model is recognized as an isolated numeral. After normalizing and binarizing the images, gradient features are extracted and recognized using SVMs. Finally, a post-processing is proposed by based on the optimal combinations of the recognition probabilities for each model. Experiments were conducted on the CENPARMI Arabic, Dari, and Urdu touching numeral pair databases[1,12].
机译:在本文中,我们提出了一种对离线无约束阿拉伯手写数字进行分割和识别的新方法,该方法无法通过关联成分分析进行分割。在我们的方法中,当选择一组参数时,触摸数字会自动分段。每个数字对具有不同参数集的模型旨在进行识别。每个模型中的每个图像都被视为一个独立的数字。在对图像进行归一化和二值化后,使用SVM提取并识别梯度特征。最后,基于每个模型的识别概率的最佳组合,提出了一种后处理方法。在CENPARMI阿拉伯数字,Dari和Urdu触摸数字对数据库上进行了实验[1,12]。

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