A multiple secret image embedding in dynamic ROI keypoints based on hybrid Speeded Up Scale Invariant Robust Features (h-SUSIRF) algorithm


  • Suganthi Kumar Vellore Institute of Technology
  • Rajkumar Soundrapandiyan


This paper presents a robust and high-capacity video steganography framework using a hybrid Speeded Up Scale Invariant Robust Features (h-SUSIRF) keypoints detection algorithm. There are two main objectives in this method: (1) determining the dynamic Region of Interest (ROI) keypoints in video scenes and (2) embedding the appropriate secret data into the identified regions. In this work, the h-SUSIRF keypoints detection scheme is proposed to find keypoints within the scenes. These identified keypoints are dilated to form the dynamic ROI keypoints. Finally, the secret images are embedded into the dynamic ROI keypoints’ locations of the scenes using the substitution method. The performance of the proposed method (PM) is evaluated using standard metrics Structural Similarity Index Measure (SSIM), Capacity (Cp), and Bit Error Rate (BER). The standard of the video is ensured by Video Quality Measure (VQM). To examine the efficacy of the PM some recent steganalysis schemes are applied to calculate the detection ratio and the Receiver Operating Characteristics (ROC) curve is analyzed. From the experimental analysis, it is deduced that the PM surpasses the contemporary methods by achieving significant results in terms of imperceptibility, capacity, robustness with lower computational complexity.




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