A hybrid-algorithm-based region of interest segmentation in THz imaging

Yuye Wang; Zhongcheng Sun; Limin Wu; Longhuang Tang; Degang Xu; Tunan Chen; Hua Feng; Jianquan Yao

doi:10.1117/12.2538890

18 November 2019 A hybrid-algorithm-based region of interest segmentation in THz imaging

Yuye Wang, Zhongcheng Sun, Limin Wu, Longhuang Tang, Degang Xu, Tunan Chen, Hua Feng, Jianquan Yao

Proceedings Volume 11196, Infrared, Millimeter-Wave, and Terahertz Technologies VI; 111960A (2019) https://doi.org/10.1117/12.2538890
Event: SPIE/COS Photonics Asia, 2019, Hangzhou, China

Abstract

Region of interest segmentation is essential for computer aided application of THz imaging. However, THz images is severely degraded by motion blur, poor resolution and noise. A robust, accurate and time-saving algorithm is in dire need for the ROI segmentation of THz images. Recently, ROI segmentation of THz-TDS images and passive THz images has been widely studied. While the ROI segmentation of THz continuous wave (CW) image is still in its infancy. In this paper, we proposed a hybrid ROI segmentation method for THz CW images. The hybrid method combines block match 3D denoising, fuzzy c-means clustering, morphology operation and canny edge detection. The hybrid method is implemented to two images acquired with a THz CW reflection imaging system. To evaluate the performance of our algorithm, we calculated the accuracy, sensitivity and specificity. As the result indicates, this hybrid ROI segmentation method performs well for THz images.

Citation Download Citation

Yuye Wang, Zhongcheng Sun, Limin Wu, Longhuang Tang, Degang Xu, Tunan Chen, Hua Feng, and Jianquan Yao "A hybrid-algorithm-based region of interest segmentation in THz imaging", Proc. SPIE 11196, Infrared, Millimeter-Wave, and Terahertz Technologies VI, 111960A (18 November 2019); https://doi.org/10.1117/12.2538890

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KEYWORDS

Image segmentation

Terahertz radiation

Denoising

Imaging systems

Tumors

Digital filtering

Brain

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