Document segmentation using wavelet-domain multi-state hidden Markov models

Jin-ping Song, Xiaoyi Yang, Yuhua Hou, Y.Y. Tang
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引用次数: 2

Abstract

Presents a document segmentation algorithm, called context-adapted wavelet-domain hidden Markov tree (CAHMT) model, which extends the wavelet-domain hidden Markov tree (HMT) model. The proposed CAHMT can achieve more accurate quality with low computation complexity in document segmentation. In addition to further improving the segmenting performance, we combine a differential operator and the lowest frequency subband with CAHMT and produce much better visual segmentation quality than the HMT.
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基于小波域多态隐马尔可夫模型的文档分割
提出了一种基于上下文的小波域隐马尔可夫树(CAHMT)模型,该模型是对小波域隐马尔可夫树模型的扩展。本文所提出的CAHMT算法在文档分割中具有较低的计算复杂度和较高的分割精度。除了进一步提高分割性能外,我们还将差分算子和最低频率子带与CAHMT相结合,产生了比HMT更好的视觉分割质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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