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Applying the Neuronetchic Methodology to Text Images for Their Recognition

机译:将神经曲法方法应用于其识别的文本图像

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There is considered the methodology for recognizing text images based on neural networks, methods and algorithms for building a neuro-fuzzy system for recognizing text images, in particular methods for improving the quality of text images and reducing noise through linear and nonlinear filtration. Features of binarization of such images, fuzzy processing of images to allocate boundaries and segmentation of symbols, and the ability to implement grammar for the structural recognition of text images is shown. The simulation of the developed system is also carried out.
机译:考虑了基于神经网络,用于构建神经模糊系统的神经网络,方法和算法来识别文本图像的方法,以识别文本图像,特别是通过线性和非线性过滤来改善文本图像的质量和降低噪声的方法。示出了这样的图像二值化的特征,示出了图像的模糊处理来分配符号的边界和分割,以及用于实现文本图像的结构识别的语法的能力。还进行了开发系统的模拟。

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