The proposed scheme utilized H.264/AVC video format for steganography which is the most common video standard at present. The scheme employed Discrete Wavelet Transform (DWT) on the Region of Interest (ROI) based on multiple moving objects tracking. After tracking multiple objects, each object is embedded with different secret images to improve the capacity. Multiple object tracking helps in achieving robustness and security; in addition, secret data is encrypted before embedding to provide a high level of security. The proposed scheme is tested on numerous video sequences by evaluating both subjective and objective metrics. Different metrics employed for objective evaluation involves Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity (SSIM) Index, Normalized Cross Correlation (NCC) and Bit Error Rate (BER). However, subjective evaluation is carried out by visual inspection. Additionally, the proposed scheme has been tested against noise, compression, frame rate change and scaling attacks to ensure robustness. Further, the security performance has been analysed by testing against three existing steganalysis techniques and histogram analysis. The main aim of the paper is to focus on robustness and security without compromising hiding capacity and imperceptibility. The reckoning result proves not only high robustness and security but also improves imperceptibility and capacity.

所提出的方案利用H.264 / AVC视频格式进行隐写术，这是目前最常见的视频标准。该方案基于对多个运动对象的跟踪，在感兴趣区域（ROI）上采用了离散小波变换（DWT）。跟踪多个对象后，将每个对象嵌入不同的秘密图像以提高容量。多对象跟踪有助于实现鲁棒性和安全性；另外，机密数据在嵌入之前经过加密，以提供高度的安全性。通过评估主观和客观指标，在众多视频序列上对提出的方案进行了测试。用于客观评估的不同度量标准涉及峰值信噪比（PSNR），均方误差（MSE），结构相似度（SSIM）指数，归一化互相关（NCC）和误码率（BER）。然而，主观评价通过目测进行。此外，已针对噪声，压缩，帧频变化和缩放攻击对提出的方案进行了测试，以确保鲁棒性。此外，已经通过针对三种现有的隐写分析技术和直方图分析进行测试来分析安全性能。本文的主要目的是着眼于鲁棒性和安全性，而不影响隐藏能力和隐身性。计算结果不仅证明了高鲁棒性和安全性，而且还提高了感知能力和容量。通过针对三种现有的隐写分析技术和直方图分析进行测试，分析了安全性能。本文的主要目的是着眼于鲁棒性和安全性，而不影响隐藏能力和隐身性。计算结果不仅证明了高鲁棒性和安全性，而且还提高了感知能力和容量。通过针对三种现有的隐写分析技术和直方图分析进行测试，分析了安全性能。本文的主要目的是着眼于鲁棒性和安全性，而不影响隐藏能力和隐身性。计算结果不仅证明了高鲁棒性和安全性，而且还提高了感知能力和容量。