How to convert an image to the cartesian X,Y coordinates?
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I have a grayscale image and i want to convert to the cartesian X,Y coordinates
2 件のコメント
Here is a small 3x3 example of a grayscale image
>> A=diag(randi(255,1,3))
A =
233 0 0
0 162 0
0 0 25
What would be the result of the "conversion" you are looking for in the case of this image.
George
2013 年 6 月 19 日
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その他の回答 (2 件)
Alex Taylor
2013 年 6 月 19 日
編集済み: John Kelly
2014 年 5 月 27 日
If what you are trying to do is reference a 2-D image to a cartesian coordinate system, you should look at the class imref2d that ships with the Image Processing Toolbox as of R2013a
For example, if you want to reference the image A that Matt mentioned to the default (Intrinsic) coordinate system used by MATLAB in which the center of the first pixel is located at position (1,1) and each pixel has an extent of one unit, you could use the following syntax of imref2d:
A=diag(randi(255,1,3));
imref2d(size(A))
ans =
imref2d with properties:
XWorldLimits: [0.5000 3.5000]
YWorldLimits: [0.5000 3.5000]
ImageSize: [3 3]
PixelExtentInWorldX: 1
PixelExtentInWorldY: 1
ImageExtentInWorldX: 3
ImageExtentInWorldY: 3
XIntrinsicLimits: [0.5000 3.5000]
YIntrinsicLimits: [0.5000 3.5000]
imref2d also provides other construction syntaxes and writable properties if you want to reference your image to some other cartesian system.
imref2d provides various methods for converting two and from image subscripts and locations in a continuous cartesian system:
>> methods(imref2d)
Methods for class imref2d:
contains intrinsicToWorld worldToIntrinsic
imref2d sizesMatch worldToSubscript
Unimaginative solution below, possibly with extra computational overhead than a direct solution using reshape and some simple calculations for the X,Y cooridnates.
A=diag(randi(255,1,3))
A =
10 0 0
0 226 0
0 0 233
>> B = true(size(A))
B =
1 1 1
1 1 1
1 1 1
stats = regionprops(B, A, 'PixelValues' , 'PixelList');
PixelListValues = cat(2, [stats.PixelList] , [stats.PixelValues])
PixelListValues =
1 1 10
1 2 0
1 3 0
2 1 0
2 2 226
2 3 0
3 1 0
3 2 0
3 3 233
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