一种基于粒子群优化的文档偏斜校正新方法

J. Sadri, M. Cheriet
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引用次数: 24

摘要

本文提出了一种新的文档歪斜校正方法。将偏斜校正建模为一个优化问题,首次采用粒子群算法求解偏斜优化问题。定义了基于投影轮廓的局部极小值和最大值的新目标函数,利用粒子群算法寻找使局部极小值和最大值之差最大化的最佳角度。在我们的方法中,局部极小值和最大值收敛于线的位置和线之间的空间。我们的歪斜校正算法的结果显示在不同的文字,如拉丁语和阿拉伯语相关的文字(如阿拉伯语,波斯语,乌尔都语,…)。实验表明,该算法可以处理大范围的倾斜角度,对不同文字的灰度图像和二值图像具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Approach for Skew Correction of Documents Based on Particle Swarm Optimization
This paper presents a novel approach for skew correction of documents. Skew correction is modeled as an optimization problem, and for the first time, Particle Swarm Optimization (PSO) is used to solve skew optimization. Anew objective function based on local minima and maxima of projection profiles is defined, and PSO is utilized to find the best angle that maximizes differences between values of local minima and maxima. In our approach, local minima and maxima converge to the locations of lines and spaces between lines. Results of our skew correction algorithm are shown on documents written in different scripts such as Latin and Arabic related scripts (e.g. Arabic, Farsi,Urdu,...). Experiments show that our algorithm can handle a wide range of skew angles, also it is robust to gray level and binary images of different scripts.
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