Problem Statement: To highlight specific aspects of an X-Ray image for further analysis using Image processing techniques.
Tools: Python, Numpy, Pandas, MATLAB, OpenCV
Concepts: Gaussian Filter, Histogram Equalization, Border Enhancement, Axial Filters, Frequency domain filters and multiple other image enhancement techniques
To
December 2022
From
July 2022
Tasks:
Different tasks involve different functions to perform on the problem statement given.
For example the first task requires us to apply the appropriate filters(Median, Mean) to even out the values in each pixel and make the contrast of the image even more uniform.
In the second task, we apply the Min and Max filters to only see pixels in a particular range of Intensity values so that we can specifically target the rib-cage area to notice any anomalies.
We also perform a series of functions to specifically highlight the borders of the rib-cage to make demarcation of the internal aspects more clearer.
Different filters are then used to compare and contrast the quality of these images and use the best one for analysis.
Conclusion:
I obtained the X-Ray image with the best quality and utility by applying a Gaussian noise filter, followed by border enhancement techniques, and finally utilizing an array flattening method.
This image was then compressed and declared as the most suitable image for identification and analysis purposes.