Passive terahertz image segmentation algorithm

Zhang Xin; Zhao Yuanmeng; Zhang Cunlin

doi:10.3788/HPLPB20132506.1597

Volume 25 Issue 06

Apr. 2013

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Article Navigation > High Power Laser and Particle Beams > 2013 > 25(06): 1597-1600

Zeng Shuguang, Zhang Bin, Sun Nianchun, et al. Chirp-matching OPCPA scheme for eliminating pre-pulse of ultrashort laser pulse[J]. High Power Laser and Particle Beams, 2012, 24: 394-398. doi: 10.3788/HPLPB20122402.0394

Citation:

Zhang Xin, Zhao Yuanmeng, Zhang Cunlin. Passive terahertz image segmentation algorithm[J]. High Power Laser and Particle Beams, 2013, 25: 1597-1600. doi: 10.3788/HPLPB20132506.1597

Citation:

Zhang Xin, Zhao Yuanmeng, Zhang Cunlin. Passive terahertz image segmentation algorithm[J]. High Power Laser and Particle Beams, 2013, 25: 1597-1600. doi: 10.3788/HPLPB20132506.1597

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Passive terahertz image segmentation algorithm

doi: 10.3788/HPLPB20132506.1597

1.
Key Laboratory of Terahertz Optoelectronics,Ministry of Education,Beijing Key Laboratory for Terahertz Spectroscopy and Imaging,Department of Physics,Capital Normal University,Beijing 100048,China

Received Date: 2012-11-20
Rev Recd Date: 2013-01-17
Publish Date: 2013-04-08

Abstract

Abstract

This study puts forward an image segmentation algorithm for passive terahertz images. First of all, the captured original terahertz images are denoised in the preprocessing course. Afterwards, we select the seed regions and the growing criteria by analysis and curve fitting of the gray histogram of the denoised images, and then carry out region growing. Experiment results show that the proposed algorithm is able to extract regions of interest from background effectively, which could help to detect the contrabands hidden under the clothes of the target subjects quickly and accurately, and consequently strengthen the practicability of our imaging system.
- passive terahertz imaging,
- image segmentation,
- curve fitting,
- region growing

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