Abstract: After reviewing the merits and drawbacks of the existing ToC ( table of contents) recognition methods, the authors describe an automatic ToC recognition method with high efficiency and adaptability. Based on style consistency of ToC in book documents, this method employs clustering to detect decorative elements and to generate an adaptive ToC model which can be used to extract ToC entries and their hierarchies. Experimental results show that this method achieves high accuracy and efficiency. Especially, it performs well in processing complicated ToC with decorative elements, broken lines and various hierarchical structures. This method has been successfully applied in a commercial E-book production line.

Key words: table of contents recognition, document logical structure, document analysis and understanding, clustering

摘要： 分析了目录识别研究的现状, 在总结当前技术优缺点的基础上, 提出了一种适应性和效率兼顾的目录识别方法。根据图书目录具有风格一致性的特点, 利用聚类技术发现目录装饰性内容, 生成具有自适应性的目录布局模型, 然后利用该模型生成目录条目及其层次关系。实验结果表明, 该方法在准确度和效率上均取得了较好的效果, 尤其是有效地处理了存在装饰性内容、折行和多种层次布局的复杂目录。该方法已应用于电子图书生产线, 显著提高了原电子目录制作系统的生产效率。

关键词: 目录识别, 文档逻辑结构, 文档分析和理解, 聚类