This paper presents a hardware implementation of a secure and reliable k-out-of-n threshold based secret image sharing method. The secret image is divided into n image shares so that any k image shares are sufficient ...
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ISBN:
(纸本)9780769534343
This paper presents a hardware implementation of a secure and reliable k-out-of-n threshold based secret image sharing method. The secret image is divided into n image shares so that any k image shares are sufficient to reconstruct the secret image in a lossless manner, but (k-1) or fewer image shares cannot reveal anything about the secret image. This secret sharing method comprises multiple independent computations which are conducive to parallelprocessing architectures. Fine-grained field programmable gate array (FPGA) architectures are the near optimal hardware platform for performing parallelprocessing. This paper illustrates the design and implementation of the secret image sharing method for 8-bit grayscale images on an FPGA which enhances execution time. On average, it was found that the FPGA. executes image sharing and reconstruction approximately 300 times faster than a microprocessor operating on the same image.
A heterogeneous system for imageprocessing was designed. The system consists of two layers with an array of DSPs in the low level layer and an array of PCs in the high level layer. The system resembles two stage mult...
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ISBN:
(纸本)0819425885
A heterogeneous system for imageprocessing was designed. The system consists of two layers with an array of DSPs in the low level layer and an array of PCs in the high level layer. The system resembles two stage multi-layers architecture. In the preprocessing phase, image data is delivered to the low level processors and operations are handled by using SPMD paradigm. The processed data is delivered to the high level processors where feature extraction and recognition tasks are performed. Apparently, the performance of this system is highly depended on communication mechanism used. The communication between two heterogeneous processing layers is a critical design issue and will be described in this paper. In our design, we have employed QuickRing. QuickRing provides a high transfer rate, 160Mbytes/s, and supports Multicast mode of data transmission that is suitable for broadcasting of data.
A presentation is made of a distributedprocessing system for motion analysis in Computer Vision. Computer Analysis of motion requires a large volume of computational efforts and real time computation is crucial to se...
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A presentation is made of a distributedprocessing system for motion analysis in Computer Vision. Computer Analysis of motion requires a large volume of computational efforts and real time computation is crucial to several applications. A description is given of architecture of a distributedprocessing system so that a serial algorithm for motion analysis could be transformed into a ″pseudo-parallel″ form.
This paper studies the application of preconditioned conjugate gradient methods in high resolution color image reconstruction problems. The high resolution color images are reconstructed from multiple undersampled, sh...
ISBN:
(纸本)0769505716
This paper studies the application of preconditioned conjugate gradient methods in high resolution color image reconstruction problems. The high resolution color images are reconstructed from multiple undersampled, shifted, degraded color frames with subpixel displacements. The resulting degradation matrices are spatially variant. The preconditioners are derived by taking the cosine transform approximation of the degradation matrices. The resulting preconditioning matrices allow the use of fast transform methods. We show how the methods can be implemented on parallel computers, and toe demonstrate thee's parallel efficiency using experiments on a sixteen processor IBM SP-2.
The available literature on parallel and distributedimageprocessing is scattered and not organized for use to beginners. Thus, there is a need of concise understanding of parallel and distributedimageprocessing ar...
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Three-dimensional RF scattering calculations for objects of realistic complexity, which require parallel computational methods in order to be feasible for design tradeoff studies, are discussed. Two basic approaches t...
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Three-dimensional RF scattering calculations for objects of realistic complexity, which require parallel computational methods in order to be feasible for design tradeoff studies, are discussed. Two basic approaches to obtaining parallel speed improvements are vectorization and full parallelprocessing. In the latter category are shared-memory and distributed-memory multiprocessor machines. The approaches to parallel computation are reviewed, and the changes required to adapt RF scattering analysis to each major parallel architecture are considered. A comparison of conversion effort and execution performance is presented for representative computers.< >
In this paper, we present the implementation of a volume graphics rendering algorithm using shift-restoration operations on parallel algebraic logic (PAL) image processor. The algorithm is a parallel ray casting algor...
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ISBN:
(纸本)0819425885
In this paper, we present the implementation of a volume graphics rendering algorithm using shift-restoration operations on parallel algebraic logic (PAL) image processor. The algorithm is a parallel ray casting algorithm. In order to eliminate shading artifacts caused by inaccurate estimation of surface normal vectors, we use gray level volume instead of binary volume, and apply a low pass filter to smooth the volume object surfaces. By transforming the volume to an intermediate coordinate system to which there is a simple mapping from the object coordinate system, we solve the data redistribution problem caused by nonregular data access patterns in volume rendering. It has been proved very effective in reducing the data communication cost of the rendering algorithm on the PAL hardware.
Many vision tasks are very complex and computationally intensive. Rear time requirements further aggravate the situation. They usually involve both structured (low-level vision) and unstructured (high-level vision) co...
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ISBN:
(纸本)0819429074
Many vision tasks are very complex and computationally intensive. Rear time requirements further aggravate the situation. They usually involve both structured (low-level vision) and unstructured (high-level vision) computations. parallel approaches offer hope in this context. parallel approaches to vision tasks and scheduling schemes for their implementation receive special emphasis in this paper. Architectural issues are also addressed. The aim is to design algorithms which can be implemented on low cost heterogeneous networks running PVM. Issues connected with general purpose architectures also receive attention. The proposed ideas have been illustrated through a practical example (of eye location from an image sequence). Next generation multimedia environments are expected to routinely employ such high performance computing platforms.
Segmentation of anatomical structures, from modalities like computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound, is a key enabling technology for medical applications such as diagnostics, plannin...
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Segmentation of anatomical structures, from modalities like computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound, is a key enabling technology for medical applications such as diagnostics, planning and guidance. More efficient implementations are necessary, as most segmentation methods are computationally expensive, and the amount of medical imaging data is growing. The increased programmability of graphic processing units (GPUs) in recent years have enabled their use in several areas. GPUs can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. Furthermore, using a GPU enables concurrent visualization and interactive segmentation, where the user can help the algorithm to achieve a satisfactory result. This review investigates the use of GPUs to accelerate medical image segmentation methods. A set of criteria for efficient use of GPUs are defined and each segmentation method is rated accordingly. In addition, references to relevant GPU implementations and insight into GPU optimization are provided and discussed. The review concludes that most segmentation methods may benefit from CPU processing due to the methods' data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup. (C) 2014 The Authors. Published by Elsevier B.V.
This paper presents a method for minimizing the total elapsed time spent by n tasks running on m differents processors working in parallel. ?he developed algorithm not only minimizes the total elapsed time but also re...
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ISBN:
(纸本)0819425885
This paper presents a method for minimizing the total elapsed time spent by n tasks running on m differents processors working in parallel. ?he developed algorithm not only minimizes the total elapsed time but also reduces the idle time and waiting time of in-process tasks. This condition is very important in some applications of computer vision in which the time to finish the total process is particularly critical -quality control in industrial inspection, real-time computer vision, guided robots, .... The scheduling algorithm is based on the use of two matrices, obtained from the precedence relationships between tasks, and the data obtained from the two matrixes. The developed scheduling algorithm has been tested in one application of quality control using computer vision. The results obtained have been satisfactory in the application of different imageprocessing algorithms.
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