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This article is cited in 10 scientific papers (total 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
Citation:
V. E. Antsiperov, “Automatic target recognition for low-count terahertz images”, Computer Optics, 40:5 (2016), 746–751
Linking options:
https://www.mathnet.ru/eng/co296 https://www.mathnet.ru/eng/co/v40/i5/p746
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Abstract page: | 125 | Full-text PDF : | 43 | References: | 28 |
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