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DOI: 10.14569/IJACSA.2016.070771
PDF

FPGA implementation of filtered image using 2D Gaussian filter

Author 1: Leila kabbai
Author 2: Anissa Sghaier
Author 3: Ali Douik
Author 4: Mohsen Machhout

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 7, 2016.

  • Abstract and Keywords
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Abstract: Image filtering is one of the very useful techniques in image processing and computer vision. It is used to eliminate useless details and noise from an image. In this paper, a hardware implementation of image filtered using 2D Gaussian Filter will be present. The Gaussian filter architecture will be described using a different way to implement convolution module. Thus, multiplication is in the heart of convolution module, for this reason, three different ways to implement multiplication operations will be presented. The first way is done using the standard method. The second way uses Field Programmable Gate Array (FPGA) features Digital Signal Processor (DSP) to ensure and make fast the scalability of the effective FPGA resource and then to speed up calculation. The third way uses real multiplier for more precision and a the maximum uses of FPGA resources. In this paper, we compare the image quality of hardware (VHDL) and software (MATLAB) implementation using the Peak Signal-to-Noise Ratio (PSNR). Also, the FPGA resource usage for different sizes of Gaussian kernel will be presented in order to provide a comparison between fixed-point and floating point implementations.

Keywords: Gaussian Filter; convolution;fixed point arithmetic; Floating point arithmetic;FPGA

Leila kabbai, Anissa Sghaier, Ali Douik and Mohsen Machhout, “FPGA implementation of filtered image using 2D Gaussian filter” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070771

@article{kabbai2016,
title = {FPGA implementation of filtered image using 2D Gaussian filter},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070771},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070771},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {7},
author = {Leila kabbai and Anissa Sghaier and Ali Douik and Mohsen Machhout}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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