Concealed object segmentation based on maximum two-dimensional entropy for passive terahertz security
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    Abstract:

    A method of the concealed object segmentation based on maximum two-dimensional entropy for passive terahertz security is proposed. The method firstly employs a filter bank to reduce image noise. A self-generated detection region algorithm is designed, which can automatically cover the key detection area. The concept of two-dimensional entropy is introduced to implement the concealed object segmentation. Evaluation and comparison experiments are conducted in 0.2 THz band passive images, demonstrating that the method has a good segmentation performance and real-time performance. It may have an important application in the automatic detection for terahertz security.

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徐华晟,李 超,方广有.基于最大二维熵的被动式太赫兹安检目标分割[J]. Journal of Terahertz Science and Electronic Information Technology ,2021,19(4):660~665

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History
  • Received:November 13,2020
  • Revised:January 07,2021
  • Adopted:
  • Online: August 25,2021
  • Published: