Image Processing is used to modify pictures to
improve their quality and extract structured information. The
need to process them in real time has lead to implement them
in hardware. To implement image processing algorithms using
high level languages requires thousands of lines of code which is
inefficient as it takes more time. Alternate solution is using Xilinx
System Generator, which is a modeling tool where design is
captured by using xilinx blockset from library environment. The
main advantage of system generator is Xilinx blocksets provide
close integration with MATLAB Simulink that helps in cosimulating FPGA module with pixel vector provided by
MATLAB Simulink blocks. The image analysis plays an
important role in medical imaging. This paper provides image
analysis of a CT scan image. The algorithms are performed on an
image to extract significant features such as image enhancement,
contrast stretching, negative of image, image segmentation and
detecting the edges for a CT scan image. The area and power
parameters are evaluated using reconfigurable platform -Artix-7
FPGA.

Project Proposal

1. High-level project introduction and performance expectation

Image Processing is used to modify pictures to improve their quality and extract structured information. The need to process them in real time has lead to implement them in hardware. To implement image processing algorithms using high level languages requires thousands of lines of code which is inefficient as it takes more time. Alternate solution is using Xilinx System Generator, which is a modeling tool where design is captured by using xilinx blockset from library environment. The main advantage of system generator is Xilinx blocksets provide close integration with MATLAB Simulink that helps in cosimulating FPGA module with pixel vector provided by MATLAB Simulink blocks. The image analysis plays an important role in medical imaging. This paper provides image analysis of a CT scan image. The algorithms are performed on an image to extract significant features such as image enhancement, contrast stretching, negative of image, image segmentation and detecting the edges for a CT scan image. The area and power parameters are evaluated using reconfigurable platform -Artix-7 FPGA

2. Block Diagram

3. Expected sustainability results, projected resource savings

algorithms for medical imaging. The recognition of tumours is an important aspect in medical field. This paper describes few algorithms that help in detection of tumours and gives a significance description. The report of power and area utilization used to implement them in real time. The hardware employed in this paper is a Artix-7 and Virtex-7 FPGA. The analysis is performed with defected and normal region of interest so that understanding of exact problem can be picturised easily