Image segmentation algorithm based on Markov random field(MRF) for radiography

Wei Caihua; Zhang Xiaolin; Liu Jun; Guan Yonghong

doi:10.11884/HPLPB201628.160148

Volume 28 Issue 12

Nov. 2016

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Article Navigation > High Power Laser and Particle Beams > 2016 > 28(12): 124001

Liu Yuan, Wang Lijuan, Guo Nan, et al. Central buoyant MEMS vector hydrophone of low-frequency and high sensitivity[J]. High Power Laser and Particle Beams, 2015, 27: 054102. doi: 10.11884/HPLPB201527.054102

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Wei Caihua, Zhang Xiaolin, Liu Jun, et al. Image segmentation algorithm based on Markov random field(MRF) for radiography[J]. High Power Laser and Particle Beams, 2016, 28: 124001. doi: 10.11884/HPLPB201628.160148

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Image segmentation algorithm based on Markov random field(MRF) for radiography

doi: 10.11884/HPLPB201628.160148

1.
Institute of Fluid Physics,CAEP,P.O.Box 919-105,Mianyang 621900,China

Received Date: 2016-05-27
Rev Recd Date: 2016-06-28
Publish Date: 2016-12-15

Abstract

Abstract

Boundary of different materials is one of the focus in flash X-ray radiography, low signal-to-noise ratio and microcosmic structure block the exact distilling of material boundary. In this paper, Markov random field method is researched, Markov model is used to describe the relativity between different pixels, to reduce the number of false target root in noise; through the variance of pixels in template with hollow center the energy cliques function is described, the segment result of microcosmic structure and segment precision of flash X-ray radiography are improved. Simulation shows the modified MRF method in this paper can get better segment result.
- image segmentation,
- flash X-ray radiography,
- Markov random field

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