Image processing

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Feature detection

Where features tend to include:

  • Points -
  • Blobs - smooth areas that won't (necessarily) be detected by point detection. Their approximate centers may also be considered interest points
  • Edges -
    • a relatively one-dimensional feature, though with a direction
  • Corners - Detects things like intersections and ends of sharp lines
    • a relatively two-dimensional kind of feature
  • Ridges

In comparisons between similar images, one should keep in mind that blob-centers can become interest points, gradients can become edges, etc., and that the difference to detectors can be and/or should be fuzzy.

  • Interest point - could be said to group the above and more
    • preferably has a clear definition
    • has a well-defined position
    • preferably quite reproducible, that is, stable under relatively minor image alterations such as scale, rotation, translation, brightness.
    • useful in their direct image context - endpoints, corners, intersections
  • Region of interest


See also:



Object detection

Detecting anything more complex than a point, edge, blob, or corner. Regularly by example.