• 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… 

Figures and Tables from this paper

Parallel computing in digital image processing
TLDR
The different types of parallelism in image processing i.e., data, task and pipeline parallelism are presented and three types of operators; point operators, neighborhood operators and global operators used for image processing are discussed.
Parallel Image Processing Techniques, Benefits and Limitations
TLDR
This research tried to describe the role of parallel image processing in the field of medical imaging and discussed the problems encountered to implement parallel computing in various image processing applications.
High Performance Color Image Processing in Multicore CPU using MFC Multithreading
TLDR
To utilize the multicore processor efficiently on windows platform for color image processing applications, a lock-free multithreading approach was developed using Visual C++ with Microsoft Foundation Class (MFC) support and results are presented.
Image registration techniques using parallel computing in multicore environment and its applications in medical imaging: An overview
TLDR
A comprehensive review of the existing literature available on Image registration methods based on parallel computing in Multi core architecture is provided to describe the various applications of image registration using parallel Computing in Medical imaging as it can be applied for different modalities of medical images.
Analysis of Explicit Parallelism of Image Preprocessing Algorithms—A Case Study
  • S. RaguvirD. Radha
  • Computer Science
    Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)
  • 2019
TLDR
The proposed work shows the analysis of the performance of the explicit parallelism of an image enhancement algorithm named median filtering in a multicore system and is based on primary measures like speedup time and efficiency.
Parallel computation of mutual information in multicore environment & its applications in medical image registration
TLDR
This research work proposes a proficient method to compute mutual information used for image registration using parallel computing that is able to work with different numbers of threads to take all the benefits of the processors having multiple cores like core i3, core i5,core i7 after maintaining the synchronization between cores.
Noise removal of the x-ray medical image using fast spatial filters and GPU
TLDR
This work undertake the study of noise removal techniques in medical image by using fast implementation of different digital filters, such as average, median and Gaussian filter, taking into account the data parallelism.
Survey on Medical Image Registration using Graphics Processing Unit
TLDR
The results obtained from CPU and GPU to register the two medical images are compared to minimize the cost function by implementing the process on the parallel platform.
Parallel Guided Image Processing Model for Ficus Deltoidea (Jack) Moraceae Varietal Recognition
TLDR
The computational flow design is emphasized on to enable the execution of the complex image processing tasks for Ficus deltoidea varietal recognition to be processed on parallel computing environment under multi-cores computer system.
Multithreading Image Processing in Single-core and Multi-core CPU using Java
TLDR
The performance of Java image processing applications designed with multithreading approach is explored, which shows performance is increased on single core and multiple core CPU in different ways in relation with image size, complexity of the algorithm and the platform.
...
...

References

SHOWING 1-10 OF 11 REFERENCES
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.
Using graphics devices in reverse: GPU-based Image Processing and Computer Vision
  • J. FungSteve 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.
Introduction to Parallel Programming
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.
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.
Ph
  • 1989
Using graphics devices in reverse : Gpubased image processing and computer vision , " in 2008 IEEE International Conference on Multimedia and Expo
  • 2011
Metodologías de paralelización en la supercomputadora cicese2000
    Crane , A simplified approach to image processing : classical and modern techniques
    • 1997
    ...
    ...