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  • Optimization of computer resources allocation is crucial for real-time image processing applications. One of the optimization possibilities is the use of GPU (Graphics Processing Unit) instead of CPU for computing. The article explains augmented reality application (AuRel) and the possibility of speeding-up the image pre-processing phase. Further, two image processing algorithms – threshold and convolution are tested. These algorithms are tested in various implementations from naive code performed on CPU to optimized code running on GPU.
  • Optimization of computer resources allocation is crucial for real-time image processing applications. One of the optimization possibilities is the use of GPU (Graphics Processing Unit) instead of CPU for computing. The article explains augmented reality application (AuRel) and the possibility of speeding-up the image pre-processing phase. Further, two image processing algorithms – threshold and convolution are tested. These algorithms are tested in various implementations from naive code performed on CPU to optimized code running on GPU. (en)
Title
  • Image Processing Methods Optimization by Means of GPU Computing
  • Image Processing Methods Optimization by Means of GPU Computing (en)
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  • Image Processing Methods Optimization by Means of GPU Computing
  • Image Processing Methods Optimization by Means of GPU Computing (en)
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  • RIV/00216305:26220/12:PU99489!RIV13-MSM-26220___
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  • P(ED2.1.00/03.0072), S
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  • 140491
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  • RIV/00216305:26220/12:PU99489
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  • Image processing, GPU (Graphics Processing Unit), GPGPU, CUDA, OpenCL, Augmented Reality (en)
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  • [2F2A9BC05710]
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  • Kos
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  • Kos Island, Greece
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  • Recent Researches in Communications and Computers
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  • Koubek, Tomáš
  • Škorpil, Vladislav
  • Endrle, Pavel
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  • WSEAS
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  • 978-1-61804-109-8
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  • 26220
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