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simple measure over an image

asked 2013-08-02 10:32:35 -0500

JnDnl gravatar image

updated 2013-08-02 14:21:45 -0500

Hi everyone, I Need to take a measure (euclidean distance) over a set of selected points on an image. In order to make this simple I broke down all the process in steps:

  1. Taking/Loading a photo (with a known pattern in it)
  2. Recognicing the pattern to calibrate measure
  3. Selecting points "from" and "to" in order to measure the distance between them

For my first iteration i will load a picture (half of number 1), select the pattern manually(a rough aproximation of number 2) and select point to measure distances between them. I'm just beginig with openCV, Do I need openCV for my fist iteration?

Thanks in advance :)

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For me your question is still to vague... Do you want to find euclidean distance in 2D between points in a single image? Or do you want to get the 3D euclidean distance of two points in a space, that have been defined in two stereo photo's? Because the second approach is a lot more complicated, including camera calibration, coordinate system conversions, mapping to 3D points, ...

StevenPuttemans gravatar imageStevenPuttemans ( 2013-08-02 14:23:52 -0500 )edit

Euclidean distance in 2D between two points in a single image

JnDnl gravatar imageJnDnl ( 2013-08-02 14:59:31 -0500 )edit

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answered 2013-08-02 15:17:38 -0500

ximobayo gravatar image

So if you know the points with their (x,y) e.g. (x1,y1) and (x2,y2)
the distance is sqrt((x2-x1)^2+(y2-y2)^2)

If you mean the 2d spatial distance in the image.

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Yes. The user will define the points over the image, so I will know their coordinates

JnDnl gravatar imageJnDnl ( 2013-08-02 15:34:43 -0500 )edit

answered 2013-08-02 14:07:39 -0500

ximobayo gravatar image

Do you mean spatial distance? What you mean exactly, do you need all the distances between all the points?

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Each measure will be made between two points.

JnDnl gravatar imageJnDnl ( 2013-08-02 15:09:20 -0500 )edit

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Asked: 2013-08-02 10:32:35 -0500

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Last updated: Aug 02 '13