Improved USCT of Paired Bones Using Waveletbased Image Processing

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FPGA Implementation of a Pseudo-Chaotic Number Generator and Evaluation of its Performance

International audienceNowadays, chaos-based cryptographicprimitives are used as an alternative to classicalcryptographic primitives for data security. Indeed, thisis because the fact that there is intrinsic randomnessin chaotic signals and ease of designing robust chaosbasedcryptographic primitives. A common andimportant element in chaos-based cryptography isthe Pseudo-Chaotic Number Generator (PCNG).A variety of PCNG with software implementationhas been published in the literature. However, dueto the rapid growth of Internet of Things (IoT),it is necessary to have such primitive in hardwareimplementation such as an FPGA. In this paper weaddress the hardware implementation on SAKURA-GFPGA-board using VHDL, of one of our PCNGs thatwas designed, implemented in C code and analyzed.We realized also the implementation in Matlab,for approving our hardware implementation. Theperformance of the hardware implementation in termsof statistical tests, throughput and logic resources iscompared with some other PCNGs

Automatic USCT Image Processing Segmentation for Osteoporosis Detection

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Design and implementation on FPGA board of a chaos-based stream cipher

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FPGA Implementation of a Chaos-based Stream Cipher and Evaluation of its Performances

International audienceChaosbased stream cipher (CSC) has caught the attention of various security applications, especially for military needs and protection in Internet of Things (IoT). In fact, computing and memory resources have been suited by chaos-based stream cipher for real-time communication. In this paper, we designed a chaos-based stream cipher using a robust pseudo chaotic number generator (RPCNG). The simulation of the proposed CSC is done in VHDL using the ISE Design Suite 14.6 tool of Xilinx with finite computing precision N = 32-bit and the hardware implementation is realized on the SAKURA-G FPGA board. The proposed system requires 6036 slices LUTs as hardware cost andachieves throughput of 301.184 Mbps. It is robust against statistical attacks and thus can be used in all applications that require confidentiality

Automatic recognition processing in ultrasound computed tomography of bone

International audienceUltrasound Computed Tomography (USCT) of soft biological tissues today provides images with a high-level of resolution. The signal acquisition system using multichannel and/or multifrequency arrays performs in circular mode and the main (linear) inversion algorithms are based on compression wave propagation modeling. The main limits of these methods for bone imaging are due to the large impedance contrast between tissues, and to propagative phenomena generated through periosteal interfaces (mode conversion, attenuation). The linear inversion methods fail to provide high-level resolution images. Despite their performance and robustness, the non-linear methods are still today unsuitable for clinical applications because of the high computation time required. However, in the special case of children bone imaging, acquisition steps must be as fast as possible, with short-time exposure and low-intensity sonication. In this context, we have developed a fast-acquisition setup (1 sec.) based on a cylindrical-focusing ring antenna, and a protocol (< 5 sec.) using classical Born approximation and spatial Fourier transform. Unfortunately, the result today is a poor contrast-to-noise ratio (CNR) image. Previous work done to improve CNR used signal and image processing. This work focuses on this last point, and an automatic edge detection procedure, using Haar wavelet 2D-decompositon, combining k-means and Ostu algorithms. Results will be presented on ex vivo real bone samples and on geometrical mimicking bone phantom (Sawbones TM). An example of bone defect imaging will be presented and discussed

Automatic recognition processing in ultrasound computed tomography of bone

International audienc