Progress In Image Registration
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Transcript of Progress In Image Registration
Progress In
Image Registration
Why Registration
• In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems.
• Image registration is the process of transforming the different sets of data into one coordinate system.
• Registration is necessary in order to be able to compare or integrate the data obtained from different measurements
Example : Two Images From a Mojave Desert Sequence
Types of Registration
• Feature Based : Identifies some landmarks, lines, curves, points of high/low intensities and maps them.
• Area Based : looks at the structure of the image as a whole using correlation metrics, Fourier transforms etc.
We Use Area Based Reg.
• “In multi-cellular biological images, there are several many different points with similar values of intensity at different cells”
R. Araiza et al. 3-D Image Registration Using Fast Fourier Transformation: Potential Applications to Geoinformatics and Bioinformatics.
The Algorithm
R. Araiza et al. 3-D Image Registration Using Fast Fourier Transformation: Potential Applications to Geoinformatics and Bioinformatics.
Determining Shift
Determining Rotation
• Compute the second order moments of the images :
xdxIxxM ikjijk
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• Compare the orientations of the largest eigenvectors of the matrices formed by the second order moments.
Determining Scale
• Just divide the magnitudes of the Fourier transforms.
Current Status
• A working Code for determining the shift, rotation and scale in 2D images.
(Courtesy : Prof. Bajaj)
• We have assembled an experiment on AVS to check the quality of output of this code.
Things To Do
• Subject the 2D code to more tests.
• Extending the code to cater to 3D Images.
• Receive datasets from MDA and run the 3D code on them.
Thank You