• Computer Science, Medicine
  • Published in IEEE Trans. Image Processing 1995
  • DOI:10.1109/83.382495

Unsupervised texture segmentation using multichannel decomposition and hidden Markov models

@article{Chen1995UnsupervisedTS,
  title={Unsupervised texture segmentation using multichannel decomposition and hidden Markov models},
  author={Jia-Lin Chen and Amlan Kundu},
  journal={IEEE transactions on image processing : a publication of the IEEE Signal Processing Society},
  year={1995},
  volume={4 5},
  pages={
          603-19
        }
}
In this paper, we describe an automatic unsupervised texture segmentation scheme using hidden Markov models (HMMs). First, the feature map of the image is formed using Laws' micromasks and directional macromasks. Each pixel in the feature map is represented by a sequence of 4-D feature vectors. The feature sequences belonging to the same texture are modeled as an HMM. Thus, if there are M different textures present in an image, there are M distinct HMMs to be found and trained. Consequently… CONTINUE READING

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