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Learning OpenCV
book

Learning OpenCV

by Gary Bradski, Adrian Kaehler
September 2008
Beginner to intermediate content levelBeginner to intermediate
580 pages
20h 7m
English
O'Reilly Media, Inc.
Content preview from Learning OpenCV

LogPolar

For two-dimensional images, the log-polar transform [Schwartz80] is a change from Cartesian to polar coordinates:

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, where

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and

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. Next, to separate out the polar coordinates into a (ρ, θ) space that is relative to some center point (xc, yc), we take the log so that

image with no caption

and

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. For image purposes—when we need to "fit" the interesting stuff into the available image memory—we typically apply a scaling factor m to ρ. Figure 6-15 shows a square object on the left and its encoding in log-polar space.

The log-polar transform maps (x, y) into (log(r),θ); here, a square is displayed in the log-polar coordinate system

Figure 6-15. The log-polar transform maps (x, y) into (log(r),θ); here, a square is displayed in the log-polar coordinate system

The next question is, of course, "Why bother?" The log-polar transform takes its inspiration from the human visual system. Your eye has a small but dense center of photoreceptors in its center (the fovea), and the density of receptors fall off rapidly (exponentially) from ...

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Publisher Resources

ISBN: 9780596516130Supplemental ContentErrata Page