Open AccessTHz linear array scanner in application to the real-time imaging and convolutional neural network recognition
Author(s) -
А. Г. Голенков,
A. V. Shevchik-Shekera,
Mykola Kovbasa,
I.O. Lysiuk,
M.V. Vuichyk,
С. В. Коринец,
С. Г. Бунчук,
S.E. Dukhnin,
Vladimir P. Reva,
Fiodor F. Sizov
Publication year - 2021
Publication title -
semiconductor physics, quantum electronics and optoelectronics/semiconductor physics quantum electronics and optoelectronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.185
H-Index - 2
eISSN - 1605-6582
pISSN - 1560-8034
DOI - 10.15407/spqeo24.01.090
Subject(s) - scanner , detector , raster scan , optics , diode , dynamic range , image sensor , amplifier , image resolution , computer science , materials science , physics , cmos , optoelectronics
Room temperature linear arrays (up to 160 detectors in array) from silicon metal- oxide-semiconductor field-effect transistors (Si-MOSFETs) have been designed for sub- THz (radiation frequency 140 GHz) close to real-time direct detection operation scanner to be used for detection and recognition of hidden objects. For this scanner, the optical system with aspherical lenses has been designed and manufactured. To estimate the quality of optical system and its resolution, the system modulation transfer function was applied. The scanner can perform real-time imaging with the spatial resolution better than 5 mm at the radiation frequency 140 GHz and contrast 0.5 for the moving object speed up to 200 mm/s and the depth of field 20 mm. The average dynamic range of real time imaging system with 160-detector linear array is close to 35 dB, when the sources with the output radiation power of 23 mW (IMPATT diodes) are used (scan speed 200 mm/s). For the system with 32-detector array, the dynamic range was about 48 dB and for the single-detector system with raster scanning 80 dB with lock-in amplifier. However, in the latter case for obtaining the image with the sizes 20×40 mm and step of 1 mm, the average scanning time close to 15 min is needed. Convolutional neural network was exploited for automatic detection and recognition of hidden items.