基于互子空间修剪方法的超低分辨率字符识别系统

Shuhei Toba, H. Kudo, Tomo Miyazaki, Yoshihiro Sugaya, S. Omachi
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引用次数: 2

摘要

字符识别技术的进步为移动相机带来了各种各样的字符识别应用。然而,由于相机的性能或环境的影响,存在许多低分辨率和低质量的字符图像,现有的方法并不擅长识别这些低分辨率字符。因此,我们开发了一个针对20*20像素以下的超低分辨率字符图像的字符识别系统。该系统包括三个阶段:使用生成式学习方法增加训练数据,使用维纳滤波和图像对齐创建去模糊的高分辨率图像,以及通过修剪互子空间方法进行识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ultra-low resolution character recognition system with pruning mutual subspace method
Improvement of character recognition technology brings us various character recognition applications for mobile camera. However, many low-resolution and poor-quality character images exist due to the performance of the camera or the influence of environment, and existing methods are not good at recognizing those low-resolution characters. Therefore, we develop a character recognition system for ultra-low resolution character images less than 20*20 pixels. The proposed system consists of three phases: increased training data with a generative learning method, creating a deblurred high-resolution image with Wiener filter and image alignment, and recognition by pruning Mutual Subspace Method.
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