基于变异函数分形维数的字体识别

A. Hajiannezhad, S. Mozaffari
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引用次数: 3

摘要

本文主要研究波斯语、阿拉伯语和英语文档的字体识别问题。它将字体识别视为纹理识别任务,提取的特征与文档内容无关。所提出的方法是基于一种分形维数技术,即方差分析。使用RBF和KNN分类器对波斯语字体的平均识别率分别为%95.5,%96,阿拉伯语字体的平均识别率为% 96.9,%98.84,英语字体的平均识别率为% 98.21,%99.6。与已有算法相比,该算法最大的优点是特征维数低、计算复杂度低、速度快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Font recognition using Variogram fractal dimension
This paper is dealing with font recognition problem in Farsi, Arabic, and English documents. It considers font recognition as texture identification task and the extracted features are independent of document content. The proposed method is based on one of the fractal dimension techniques which is called Variogram Analysis. The average recognition rates using RBF, and KNN classifiers are respectively %95.5, %96 for Farsi fonts, and % 96.9, %98.84 for Arabic fonts, and % 98.21, %99.6 for English fonts. The most important advantages of our algorithm are low feature dimensions, low computational complexity, and high speed compared with the previous efforts.
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