A Multi-Thresholding Method Based on Otsu’s Algorithm for the Detection of Concealed Threats in Passive Millimeter-Wave Images

Abstract In this study, an algorithm to the detection and imaging of hidden arms for passive millimeter-wave (PMMW) imaging systems is proposed. This technique is; in fact, an improved version of our previously developed auto-classification algorithm by extending it by exploiting the Otsu’s multi-level thresholding method. The detailed derivation and the brief steps of the proposed algorithm are given. The proposed algorithm is tested and validated by real PMMW images obtained by a real radiometric imaging system. Resultant measured images are obtained with the employment of signal and image processing procedures of the suggested technique. It is demonstrated by the constructed PMMW images that proposed technique successfully detects a concealed metal threat and also predicts its size by drawing the shape outline based on Otsu’s multi-level thresholding routine that was specially tailored to our auto-classification technique.

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