Comments on: Spatial transformations: Translation confusion

By: Steve Eddins

Steve Eddins — Thu, 29 Dec 2011 13:18:40 +0000

Einat—In the imtransform documentation, see the "Pure translation" section under "Tips."

By: Einat

Einat — Tue, 27 Dec 2011 20:40:50 +0000

Finally found this solution! Been looking for this for so long! thanks. Would be nice if it was mentioned as part of the Help for “cpselect” and “imtransform” :)

By: Steve

Steve — Tue, 10 Aug 2010 16:53:23 +0000

Chew—You’ll need to say more. What exactly did you try, and why were the results not satisfactory?

By: Chew

Chew — Tue, 10 Aug 2010 15:13:53 +0000

I am trying to model simple translation on the image by step of non-integer value (eg 2.5 pixel). I was hoping if you can provide me some guidance as I tried imtransform of that translation matrix and using bicubic interpolation but the image is different that expected. There are shades that wasn’t supposed to be there. Hope to hear from you soon.

Thanks.

Regards,
Chew

By: Steve

Steve — Tue, 13 Jul 2010 15:55:43 +0000

Chris—Thanks for your input. We recognize that the automatic scale change behavior in imtransform is frequently confusing and we are taking steps to address this.

By: Chris

Chris — Tue, 13 Jul 2010 14:52:07 +0000

I noticed you are looking for recommendations on how to implement imtransform. I would recommend an optional parameter in imtransform that causes the returned image to be exactly what is expected, including the expected translation and one-to-one pixel mapping. I know there is a concern about exceeding memory limitations, but if this occurs, the error Matlab gives is very clear on the cause of the error.

By: Chris

Chris — Tue, 13 Jul 2010 14:13:43 +0000

Of course, I figured it out shortly after sending that message. The relatively large distance between my basePoints and inputPoints increases the condition number and triggers imtransform to stop mapping pixels 1-to-1 in order to reduce output image size. By using

imtransform(...,'XYScale',1)

the problem is fixed. Documented feature.

By: Steve

Steve — Tue, 13 Jul 2010 12:35:50 +0000

Chris—Please contact technical support.

By: Chris

Chris — Mon, 12 Jul 2010 20:12:01 +0000

The code below illustrates a problem I'm having with imtransform. I do not see why I get a correct transform with the first set of input points, but not with the second set. Also, I don't know what it is about the four pairs of control points that make the condition number so high. Any help or ideas would be greatly appreciated.

close all;clear all;

% User inputs
inputSet = 2;           % 1 for a set of input points that works, 2 for a set that does not work
numRows = 378;          % Rows in original image
numCols = 570;          % Cols in original image
featureRow = 370;    % Row location of a feature
featureCol = 560;    % Col location of a feature

% Define basePoints and inputPoints
basePoints =[143    95; 428    95; 143   284; 428   284];
if inputSet == 1
    inputPoints = [-2715.562638664548   388.123635347757; -2125.110248447010 397.956744564281; ...
        -2687.235992046404 670.251779320847; -2109.030835350265 646.991296648817];
elseif inputSet == 2  
    inputPoints = [-2841.364192843382   392.571575290416; -2232.168660713694 402.270514363645; ...
        -2811.962711649763 679.351410803620; -2215.607991122505 654.591857089487];
    % Note: inputSet 2 works if you remove the average row and column locations in inputPoints 
    % (commented out below). I don't understand why this should make a difference
        % inputPoints(:,1) = inputPoints(:,1) - mean(inputPoints(:,1));
        % inputPoints(:,2) = inputPoints(:,2) - mean(inputPoints(:,2));
end

% Plot basePoints and inputPoints
figure;plot(basePoints(:,1),basePoints(:,2),'b+');
hold on;
plot(inputPoints(:,1),inputPoints(:,2),'g+');

% Compute tform
tform = cp2tform(inputPoints,basePoints,'projective');

% Compute condition number.  It is very high, even though this appears to be a straightforward 
% transform (see plot above)
conditionNum = cond(tform.tdata.T)

% Create image.  Outlined with 1's.  Feature is a 3x3 region of 2's.
originalImage = zeros(numRows,numCols);
originalImage(1,:) = 1;
originalImage(numRows,:) = 1;
originalImage(:,1) = 1;
originalImage(:,numCols) = 1;
originalImage(featureRow-1:featureRow+1,featureCol-1:featureCol+1,:) = 2;

% Transform the image
[tformedImage,colData,rowData] = imtransform(originalImage,tform,'nearest');

% Locate the feature
[rowIndices,colIndices] = find(tformedImage(:,:,1)==2);
tformedFeatureCol = colData(1) + mean(colIndices) - 1
tformedFeatureRow = rowData(1) + mean(rowIndices) - 1

% Now perform a manual calculation of where the feature should be located
tformedPoint = tform.tdata.T'*[featureCol;featureRow;1];
expectedTformedCol = tformedPoint(1)/tformedPoint(3)
expectedTformedRow = tformedPoint(2)/tformedPoint(3)

% Compute error in feature location
colError = tformedFeatureCol - expectedTformedCol
rowError = tformedFeatureRow - expectedTformedRow

By: Steve

Steve — Thu, 25 Mar 2010 18:45:02 +0000

If you can successfully segment the object, then you can assign its pixel values somewhere else in the image. Of course, you’ll have to fill in the gap in the original object location. You might take a look at roifill.