基于SVM区域构造的复杂中文版面分析

针对现有的版面分析算法对参数的敏感性以及弱适用性等缺陷，提出基于SVM区域构造的复杂中文文档版面分析算法。该算法通过选取最能代表区域字符特征的连通区(种子连通区)作为测试的第一特征，利用具有强学习和泛化能力的支持向量机实现区域构造，在构造的区域中运用投影快速判断文档阅读顺序。实验结果表明，该方法具有更好的适应性，对复杂的中文版面有满意的分析结果。

Complex Chinese Document Layout Analysis Based on SVM Region Formation

Most existing algorithms for document layout analysis are sensitive to the parameters and have weak applicability. In order to make up these deficiencies, this paper presents an algorithm of region formation based on Support Vector Machine(SVM) for analyzing Chinese document. In the proposed technique, it selects connected components called seed connected components which can be used to represent regions as the first feature for training. SVM is employed to form region since it has strong learning and generalization ability. The technique decides the reading order by exploiting the projection method. Extensive experimental results show that the proposed algorithm is more effective to analyze different kinds of document layout than the state-of-the-art methods.