This article is cited in 10 papers

IMAGE PROCESSING, PATTERN RECOGNITION

Automatic target recognition for low-count terahertz images

V. E. Antsiperov

Kotel’nikov Institute of Radioengineering and Electronics, Moscow, Russia, Russian Academy of Sciences

Abstract: The paper presents the results of developing an algorithm for automatic target recognition in broadband (0.1-10) terahertz images. Due to the physical properties of terahertz radiation and associated hardware, such images have low contrast, low signal-to-noise ratio and low resolution – i.e. all the characteristics of a low-count images. Therefore, standard recognition algorithms designed for conventional images work poorly or are not suitable at all for the problem considered. We have developed a fundamentally different approach based on clustering 2D point clouds in accordance with a set of predefined patterns. As a result, we reduce the problem of target recognition to the problem of maximizing the image data likelihood with respect to the classes of model objects up to the size and position. The resulting recognition algorithm has a structure close to that of the well-known EM algorithm; its formal scheme is at the end of the paper.

Keywords: automatic target recognition, concealed objects detection, low-count images, THz imaging, EM-algorithm, classification, image recognition.

Received: 14.05.2016
Accepted: 16.10.2016

Language: English

DOI: 10.18287/2412-6179-2016-40-5-746-751