Dynamic variations in the ultrasound greyscale median of carotid
Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several...
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Transcript of Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several...
![Page 1: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/1.jpg)
Picture Comparison; now with shapes!
Slightly weak during MS1, only colour comparisonSeveral comparisons will be doneTurn picture into greyscale to do shape comparisonUse colour picture to do a colour histogram, and averaging/mixing
Picture Greyscale
Histogram
![Page 2: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/2.jpg)
Greyscale shapes
Use greyscale picture and take contour From the contour you can describe the shape The first way is through approximation with central
moments Centeral Moments are position invariant
Grayscale Contour
![Page 3: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/3.jpg)
The Hero Ming-Kuei Hu
Central Moments describes the polygon through probability.
Hu-Moments are based on central moments Hu-Moments are rotation and skewing invariant. Using Hu-moments to describe the polygon means it
doesn't matter how it's rotated, skewed, scaled or its position.
There is 7 Hu-moments and when you use them you get a single number for each of them, making them useful for searching.
![Page 4: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/4.jpg)
The Hero Ming-Kuei Hu
Central Moments describes the polygon through probability.
Hu-Moments are based on central moments Hu-Moments are rotation and skewing invariant. Using Hu-moments to describe the polygon means it
doesn't matter how it's rotated, skewed, scaled or its position.
There is 7 Hu-moments and when you use them you get a single number for each of them, making them useful for searching.
![Page 5: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/5.jpg)
Fourier Descriptors
Second method to describe polygons is through Fourier descriptors
Describes the polygon with approximation using waves. Each new wave makes the approximation more exact. By using lower number of waves the approximation get
rough, which at times is useful.
![Page 6: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/6.jpg)
Colour matching
Use a histogram of colours in picture to see if they have similar set of colours
Mix together colours to bigger group to get rough placement of colours.(still dependant on rotation then)
Use a fully mixed picture(one colour) and histogram, for searching.
![Page 7: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/7.jpg)
Searching
Use a rough search that is low cost Use more expensive search when they are accepted by
low cost search. Pre-process pictures and tag them for the low cost
search.
![Page 8: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/8.jpg)
OpenCV
Contours Fourier Centeral Moments(which can easily be used for Hu
moments) Histograms Picture Handling Pretty much everything I'd imagine needing
![Page 9: Picture Comparison; now with shapes! Slightly weak during MS1, only colour comparison Several comparisons will be done Turn picture into greyscale to do.](https://reader031.fdocuments.in/reader031/viewer/2022032607/56649ed85503460f94be6d61/html5/thumbnails/9.jpg)
Papers! Visual pattern recognition by moment invariants by Hu
Ming-Kuei Shape-based image retrieval using generic Fourier
descriptor by Dengsheng Zhang & Guojun Lu A comparative study of Fourier descriptors and Hu's
seven moment invariants for image recognition by Qing Chen
Robust and Efficient Fourier–Mellin Transform Approximations for Gray-Level Image Reconstruction and Complete Invariant Description by Stéphane Derrodea & Faouzi Ghorbel