Applying SGD Optimization Algorithm Method for Detecting and Localizing of Concealed Objects in Passive Millimeter-Wave Images
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Abstract
Millimeter waves have salient characteristics such as penetration through fabric fibers. These waves can be used to generate passive millimeter-wave images (PMMWIs) for detecting and localizing concealed objects under clothing. The obtained images have important applications in security systems and treat detection. These systems are installed in places such as airports, warehouses, and places that require high security. Passive millimeter-wave images are generated using passive scanners. The main challenges in these images are their incomprehensibility and low signal-to-noise ratio ant this avoids extracting good features from the images and reduces the accuracy of detecting and localizing concealed objects in the image. In this study, SGD Optimization Algorithm Method was used for detection and localizing after selecting highly ambiguous sample images. According to simulation results, our proposed method improves the classification process significantly.
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