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

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.