11076

A GPU-Accelerated Framework for Image Processing and Computer Vision

Ashwini.A.Patil, Pankaja.A.Shahapure
Department of Computer Science and Engineering, Hirasugar Institute Of Technology, Nidsoshi, Karnataka, India
International Journal of Latest Trends in Engineering and Technology (IJLTET), 2013
@article{patil2013gpu,

   title={A GPU-Accelerated Framework for Image Processing and Computer Vision},

   author={Patil, Ashwini A and Shahapure, Pankaja A},

   year={2013}

}

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This paper presents and briefly describes the state of the art of accelerating image processing with graphics hardware (GPU) and discusses some of its caveats. Then it describes GpuCV, an open source multiplatform library for GPU-accelerated image processing and Computer Vision operators and applications. It is meant for computer vision scientist not familiar with GPU technologies. GpuCV is designed to be compatible with the popular OpenCV library by offering GPU- accelerated operators that can be integrated into native OpenCV applications. The GpuCV framework transparently manages hardware capabilities, data synchronization, activation of low level GLSL and CUDA programs, on-the-fly benchmarking and switching to the most efficient implementation and finally offers a set of image processing operators with GPU acceleration available.
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