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ICNC
2005
Springer

Texture Segmentation Using Neural Networks and Multi-scale Wavelet Features

9 years 1 months ago
Texture Segmentation Using Neural Networks and Multi-scale Wavelet Features
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.
Tae-Hyung Kim, Il Kyu Eom, Yoo Shin Kim
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICNC
Authors Tae-Hyung Kim, Il Kyu Eom, Yoo Shin Kim
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