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

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.