30-06-2012, 11:33 AM
AN EFFICIENT FPGA IMPLEMENTATION OF MRI IMAGE FILTERING AND TUMOUR CHARACTERIZATION USING XILINX SYSTEM GENERATOR
[attachment=26228]
ABSTRACT
This paper presents an efficient architecture for various image filtering algorithms and tumor
characterization using Xilinx System Generator (XSG). This architecture offers an alternative through a
graphical user interface that combines MATLAB, Simulink and XSG and explores important aspects
concerned to hardware implementation. Performance of this architecture implemented in SPARTAN-3E
Starter kit (XC3S500E-FG320) exceeds those of similar or greater resources architectures. The proposed
architecture reduces the resources available on target device by 50%.
INTRODUCTION
The handling of digital images has become a subject of widespread interest in different areas
such as medical, technological applications and many others. There are lots of examples where
image processing helps to analyze, infer and make decisions. The main objective of image
processing is to improve the quality of the images for human interpretation, or the perception of
the machines independently. This paper focuses on processing an image pixel by pixel and in
modification of pixel neighbourhoods and the transformation that can be applied to the whole
image or only a partial region. The need to process the image in real time, which is time
consuming, leads to this implementation in hardware level, which offers parallelism, and thus
significantly reduces the processing time. FPGAs are increasingly used in modern imaging
applications image filtering[1,2], medical imaging[3,4], image compression[5-7], wireless
communication[8,9].The drawback of most of the methods are that they use a high level language
for coding. This objective lead to the use of Xilinx System Generator, a tool with a high- level
graphical interface under the Matlab, Simulink based blocks which makes it very easy to handle
with respect to other software for hardware description [10].
XILINX SYSTEM GENERATOR
Xilinx System Generator (XSG) [12,13] is an integrated design Environment (IDE) for FPGAs
within the ISE 11.3 development suite, which uses Simulink[14], as a development environment
and is presented in the form of model based design. It has an integrated design flow, to move
directly to the Bit stream file (*. bit) from Simulink design environment which is necessary for
programming the FPGA.
EDGE DETECTION
Edge detection [16] is one of the most commonly used operations in image analysis, and there are
probably more algorithms in literature for enhancing and detecting edges. An edge is point of
sharp change in an image, a region where pixel locations have abrupt luminance change i.e. a
discontinuity in gray level values. In other words, an edge is the boundary between an object and
the background. The shape of edges in images depends on many parameters like the depth
discontinuity, surface orientation discontinuity, reflectance discontinuity, illumination
discontinuity, and noise level in the images.
[attachment=26228]
ABSTRACT
This paper presents an efficient architecture for various image filtering algorithms and tumor
characterization using Xilinx System Generator (XSG). This architecture offers an alternative through a
graphical user interface that combines MATLAB, Simulink and XSG and explores important aspects
concerned to hardware implementation. Performance of this architecture implemented in SPARTAN-3E
Starter kit (XC3S500E-FG320) exceeds those of similar or greater resources architectures. The proposed
architecture reduces the resources available on target device by 50%.
INTRODUCTION
The handling of digital images has become a subject of widespread interest in different areas
such as medical, technological applications and many others. There are lots of examples where
image processing helps to analyze, infer and make decisions. The main objective of image
processing is to improve the quality of the images for human interpretation, or the perception of
the machines independently. This paper focuses on processing an image pixel by pixel and in
modification of pixel neighbourhoods and the transformation that can be applied to the whole
image or only a partial region. The need to process the image in real time, which is time
consuming, leads to this implementation in hardware level, which offers parallelism, and thus
significantly reduces the processing time. FPGAs are increasingly used in modern imaging
applications image filtering[1,2], medical imaging[3,4], image compression[5-7], wireless
communication[8,9].The drawback of most of the methods are that they use a high level language
for coding. This objective lead to the use of Xilinx System Generator, a tool with a high- level
graphical interface under the Matlab, Simulink based blocks which makes it very easy to handle
with respect to other software for hardware description [10].
XILINX SYSTEM GENERATOR
Xilinx System Generator (XSG) [12,13] is an integrated design Environment (IDE) for FPGAs
within the ISE 11.3 development suite, which uses Simulink[14], as a development environment
and is presented in the form of model based design. It has an integrated design flow, to move
directly to the Bit stream file (*. bit) from Simulink design environment which is necessary for
programming the FPGA.
EDGE DETECTION
Edge detection [16] is one of the most commonly used operations in image analysis, and there are
probably more algorithms in literature for enhancing and detecting edges. An edge is point of
sharp change in an image, a region where pixel locations have abrupt luminance change i.e. a
discontinuity in gray level values. In other words, an edge is the boundary between an object and
the background. The shape of edges in images depends on many parameters like the depth
discontinuity, surface orientation discontinuity, reflectance discontinuity, illumination
discontinuity, and noise level in the images.