Abstract: In this paper a watermark embedding and recovery technique based on the compressed sensing theorem is proposed. Both host and watermark images are sparsified using DWT. In recovery process, a new method called Least Support Matching Pursuit (LS-OMP) is used to recover the watermark and the host images in clean conditions. LS-OMP algorithm adaptively chooses optimum L (Least Part of support), at each iteration. This new algorithm has some important characteristics: it has a low computational complex-ity comparing with ordinary OMP method Also, we develop an invisible image watermarking algorithm in the presence of compressive sampling using the LS-OMP. Simulation results show that LS-OMP outperforms many algorithms

• Publication Date: 26-Oct-2014
• DOI: 10.15224/978-1-63248-029-3-85
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Abstract: At present there is a significant class of different personalized mobile systems for human health control. These personalized systems have been developed in order to run diagnostic procedures of patient’s health conditions. Systems like this are passive means of measuring, control, and accumulation of medical and biological information having a limited number of active tasks. The new class of medical and biological systems is originating right now; it includes active interaction between electronic components, health aids, and human organism, wider integration of instrumental and measuring system, neural-network interaction, and human in a real-time mode. The description of one of the version under development is given below. It is a personal accompanying remote noninvasive medical system based on mobile applications.

• Publication Date: 26-Oct-2014
• DOI: 10.15224/978-1-63248-029-3-86
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• Downloads: 0