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Fast digital watermarking of uncompressed colored images using bidirectional extreme learning machine

机译:使用双向极限学习机对未压缩彩色图像进行快速数字水印

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Development of fast watermarking schemes for all multimedia objects is crucial to the present day research in information security. Besides speed of execution minimizing the trade-off between visual quality and robustness is another important requirement of this research domain. In view of this, a newly developed single layer feedforward network (SLFN) commonly known as Bidirectional Extreme Learning Machine (B-ELM) is employed to carry out watermark embedding and extraction from four colored images. The results show that the B-ELM technique outperforms the previously employed ELM technique for this purpose. It is concluded that visual quality and robustness trade-off is minimized and real time targets are achieved. Thus, the proposed scheme is found to be suitable for developing video watermarking applications.
机译:为所有多媒体对象开发快速水印方案对于当今信息安全研究至关重要。除了执行速度之外,最小化视觉质量和鲁棒性之间的折衷是该研究领域的另一个重要要求。有鉴于此,采用了一种新开发的单层前馈网络(SLFN),通常被称为双向极限学习机(B-ELM),用于从四个彩色图像中进行水印嵌入和提取。结果表明,为此目的,B-ELM技术优于先前采用的ELM技术。结论是,视觉质量和鲁棒性之间的权衡最小化,并实现了实时目标。因此,发现所提出的方案适合于开发视频水印应用。

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