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Data Hiding (DH) is a widely distributed method to conceal private data through the internet. Hiding data in a Moving Object (MO) in the video has sought attention due to the deficiency of human visual structure. The existing Exploiting Modification Direction (EMD) technology faces a large amount of distortion due to the even distribution of DH. This paper proposes a Generalized Exploiting Modification Direction (GEMD) by splitting a video into compressed frames and then the frames are separated into MO. Each MO is distinguished using Kalman technique by analyzing the first and next frames. The GEMD is applied separately in each MO by interpolating the image using matching algorithm. In order to reduce the mismatch problem out of boundary pixels and error rates are considered. The proposed DH algorithm is evaluated using PETS 2009 data set. Experimental results have demonstrated that the proposed GEMD algorithm hiding data in each MO improves the capacity and image quality over the existing methods.

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Robust Data Hiding in Moving Object Videos Using Generalized Error Modification Detection (GEMD)

  • 会议论文

  • 发表日期：

    2025年

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  • R. Roselin Kiruba,
  • S. Anitha,
  • C. P. Koushik,
  • G. Dharani Devi,
  • N. Naveen Kumar,
  • L. Sharmila

摘要

Data Hiding (DH) is a widely distributed method to conceal private data through the internet. Hiding data in a Moving Object (MO) in the video has sought attention due to the deficiency of human visual structure. The existing Exploiting Modification Direction (EMD) technology faces a large amount of distortion due to the even distribution of DH. This paper proposes a Generalized Exploiting Modification Direction (GEMD) by splitting a video into compressed frames and then the frames are separated into MO. Each MO is distinguished using Kalman technique by analyzing the first and next frames. The GEMD is applied separately in each MO by interpolating the image using matching algorithm. In order to reduce the mismatch problem out of boundary pixels and error rates are considered. The proposed DH algorithm is evaluated using PETS 2009 data set. Experimental results have demonstrated that the proposed GEMD algorithm hiding data in each MO improves the capacity and image quality over the existing methods.