Why the feature should be RST invarient..when extracting a feature from an image..
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A good feature should have high varinace and it should be RST invariant for image. Why is it so?
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Walter Roberson
on 4 Apr 2013
If "RST" here stands for "Rotation, Scaling, Translation", then under what circumstances would it be beneficial to have a feature that was varient under one of those operations?
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Image Analyst
on 4 Apr 2013
One example, robots to "pick and place" parts from a bin onto an assembly they're building.
Walter Roberson
on 4 Apr 2013
True, size (scale) could be important in some contexts that involved calibrated sensors.
Image Analyst
on 4 Apr 2013
That's only true for certain situations. I'm sure you can imaging situations were you'd like them to vary and situations where you'd like them not to vary. Though I can't think of any situations where you'd want the feature measurements to have a high variance instead of a low variance. Invariant and variance are different concepts, but not antonymns (opposites) - consult a dictionary.
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