基于知识的韩文字符图像减薄算法研究

Kwak Yoonsik, Choi Kihyung
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引用次数: 0

摘要

细化算法是一种预处理技术,是图像处理技术的重要组成部分。随着其应用范围和相关领域,如字符识别系统的不断扩大,其研究也越来越活跃。朝鲜语由一个起始音素、一个中间元音和一个末音素组成。它的特点是,根据它的位置,它的大小和形状可以改变。正因为如此,更具体地说,因为这三个元素应该以某种方式组合或连接起来才能产生一个角色,所以在曲线和连接区域中会出现扭曲形状的问题。这个问题主要是由于物体像素的厚度不规则,严重影响了使用曲面和连通形状信息作为识别变量的韩文字符识别系统。本文研究了一种基于知识的韩文字符图像稀疏算法。其目的是将韩国文字形象的失真率降到最低。此外,我相信该算法不仅有助于提高字符识别系统的有效性,而且还可以应用于医学图像预处理技术,例如正在大力研究的医疗管理计算机化。
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A study on the knowledge-based thinning algorithm that preserve the shape of the Korean character image
The thinning algorithm is a preprocessing technique that is an important part of image processing techniques. As the scope of its applied and related fields, such as character recognition systems, has been wider, so has its research been active. A Korean character consists of an initial phoneme, a medial vowel and a final phoneme. It has the aspect that, according to its placement, its size and shape can be changed. Because of this, and more specifically since all three elements should be combined or connected in some way to produce a character, there occurs a problem of the distorted shape in the curved and the connected areas. This problem is mainly due to the irregular thickness of an object pixel, and seriously affects the Korean character recognition system, which uses the curved and the connected shape information for its recognition variable. This article is on a knowledge-based thinning algorithm which deals with printed Korean character images. It is intended to reduce the distortion rate of a Korean character image to its minimum level. Furthermore, I believe that this algorithm not only helps to enhance the effectiveness of the character recognition system, but it can also be applied as a medical image preprocessing technique, e.g. in the computerization of the medical administration, which is being vigorously studied.<>
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