Corpus ID: 14904116

Image Processing Tasks using Parallel Computing in Multi core Architecture and its Applications in Medical Imaging

@inproceedings{Saxena2013ImagePT,
  title={Image Processing Tasks using Parallel Computing in Multi core Architecture and its Applications in Medical Imaging},
  author={Sanjay Saxena and Neeraj Sharma and Shiru Sharma},
  year={2013}
}
To find accurate & reliable result in image analysis, it is important that image is processed and analyzed using image processing suitable AI technique further at the same time it is highly desired that processing time must be minimum. Preprocessing of the image makes it more clear and visible, while parallelizing of the algorithm optimizes the speed at which the image is processed. This paper explores current multi-core architectures available in commercial processors in order to speed up the… Expand
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References

SHOWING 1-10 OF 11 REFERENCES
A Simplified Approach to Image Processing: Classical and Modern Techniques in C
TLDR
This book provides a comprehensive introduction to the most popular image processing techniques used today, without getting bogged down in the complex mathematical presentations found in most image processing books and journals. Expand
Tutorial in Data Parallel Image Processing
TLDR
This tutorial is on real time, low level image processing for parallel active vision systems and image operator classes discussed are point operators, local operators, dithering, smoothing, edge detection, morphological operators, and image segmen-tation. Expand
Using graphics devices in reverse: GPU-based Image Processing and Computer Vision
  • J. Fung, S. Mann
  • Computer Science
  • 2008 IEEE International Conference on Multimedia and Expo
  • 2008
TLDR
This paper discusses how this processing power is being harnessed for image processing and computer vision, thereby providing dramatic speedups on commodity, readily available graphics hardware. Expand
Introduction to Parallel Programming
This chapter is an introduction to parallel programming. It is organized to address the need for teaching parallel programming on current system architectures using OpenCL as the target language, andExpand
Interactive Supercomputing’s Star-P Platform
TLDR
A classroom productivity study involving 29 students who have written a homework exercise in a low level language (MPI message passing) and a highlevel language (Star-P with MATLAB client), which indicates what perhaps should be of little surprise: the high level language is always far easier on the students than the lowlevel language. Expand
Using graphics devices in reverse : Gpubased image processing and computer vision , " in 2008 IEEE International Conference on Multimedia and Expo
  • 2011
Rasúa, “Algoritmos paralelos para la solución deproblemas de optimización discretos aplicados a ladecodificación de señales,
  • Ph.D. dissertation, Departamento de Sistemas Informáticos y Computación. Universidad Politécnica de Valencia,
  • 2009
Crane , A simplified approach to image processing : classical and modern techniques
  • 1997
Ph
  • 1989
...
1
2
...