Texture Segmentation Using Neural Networks and Multi-scale Wavelet Features

@inproceedings{Kim2005TextureSU,
  title={Texture Segmentation Using Neural Networks and Multi-scale Wavelet Features},
  author={Tae-Hyung Kim and Il Kyu Eom and Yoo Shin Kim},
  booktitle={ICNC},
  year={2005}
}
This paper presents a novel texture segmentation method using Bayesian estimation and neural networks. Multi-scale wavelet coefficients and the context information extracted from neighboring wavelet coefficients were used as input for the neural networks. The output was modeled as a posterior probability. The context information was obtained by HMT (Hidden Markov Trees) model. The proposed segmentation method shows performed better than ML (Maximum Likelihood) segmentation using the HMT model. 

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