Saliency and superpixel improved detection and segmentation of concealed objects for passive terahertz images

Sushmita Chandel; Gaurav Bhatnagar; Marcin Kowalski

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Saliency and superpixel improved detection and segmentation of concealed objects for passive terahertz images

机译：Saliency and superpixel improved detection and segmentation of concealed objects for passive terahertz images

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摘要

Application of passive terahertz imaging in concealed weapon detection has been looked at, such that the final result is the segmentation of the foreground concealed weapons from the rest of the background. For the same, a fully automatic and completely generic technique, without any learning, has been proposed. It was observed that a simple thresholding step, exploiting varied intensity bands of the tetrahertz images is not enough. Thus, an innovative method to isolate humans and thus improve the region of interest (ROI) has been proposed. Thereafter, saliency has been used to further improve ROI, as these images are quite noisy and the central focusing aspect of saliency could handle the noise around the concealed weapons. It was observed that this step could handle the noise around the concealed weapons but degraded the boundaries of the concealed weapons. To further improve boundary adherence, superpixels are used. Finally, results are evaluated both quantitatively and qualitatively and outperformed the traditional approach.

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来源
《Optical Engineering》 |2023年第2期|023101-1-023101-14|共14页
作者
Sushmita Chandel; Gaurav Bhatnagar; Marcin Kowalski;
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作者单位

Indian Institute of Technology Jodhpur (India);

Institute of Optoelectronics, Wojskowa Akademia Techniczna im. Jaroslawa Dabrowskiego (Poland);

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
Image segmentation; Weapons; Terahertz radiation; Object detection; Denoising; Optical engineering; Machine learning;

Saliency and superpixel improved detection and segmentation of concealed objects for passive terahertz images

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