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Image Segmentation Based on Multi-level MRF Markers and Mapping Rule

Yaqun Fang

Abstract


Aiming at the problem of colorful image segmentation, Markov random field (MRF) model and iterated conditional models (ICM) can be the marker by reasoning method. The multi-scale decomposition of image expression by wavelet and the top image with apriori mark access issues can improve the original spectral clustering. The automatic clustering parameter image by using affinity propagation is ensemble learning algorithm of stability and accuracy. The other scale images by analyzing the regional characteristics of change scale correlation are consistent with the similarity in different scales and in the same scale space neighborhood. The three-dimensional structure descriptions of space mapping rule has the image segmentation experiments. Through the quantitative and qualitative experimental analysis, the experiment results show that the algorithm has good accuracy, robustness and universality.

Keywords


MRF marker, mapping rule, ICM, image segmentation.

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