Brett's Pick this week is2D Line Curvature and Normals, byDirk-Jan Kroon.

Recently, I began working on an app to facilitate interactive image segmentations. Ultimately, I want to create a suite of tools that allow me to use some combination of automated and manual manipulations to create flexibly a complicated mask of my images. As part of that project, I want the ability to create closedor open (!)imfreehandorimpolyregions, and to use those regions to modify my mask.

Creating masks from closed regions is easy with theimroitools of theImage Processing Toolbox; the "createMask" method trivializes the process. But creating masks from open regions can produce some unexpected, and unwanted, results.

Suppose, for example, that I wanted to create a mask from a manual tracing of the lower left petal of the "yellow lily" image that ships with the Image Processing Toolbox:

I read in and display the image, and trace the boundary of interest:

lily = imread('C:\Program Files\MATLAB\R2015a\toolbox\images\imdata\yellowlily.jpg'); ax(1) = subplot(1,2,1); imshow(lily) title('Lovely Lily')% I did this manually, saved the positions to a Mat-file:% h = impoly(imgca,'closed',false);loadoutlinedLilyh = impoly(imgca,xsys,'closed',false); xsys = getPosition(h); xs = xsys(:,1); ys = xsys(:,2);% (Note: you can do this with |imfreehand|, too, but I find that I can be% much more accurate with |impoly|.)defaultMask = createMask(h); holdonplot(xs,ys,'r.','markersize',16);

If I simply use the createMask method, I get a mask of the filled region within the closed ROI:

ax(2) = subplot(1,2,2); imshow(defaultMask); title('Default createMask')

But that's not what I wanted! I could usebwperim(for example) on that mask, but then I would have to remove the effects of the unwanted region closing. What Ireallywanted was a thin "shell" around my drawn region, from which I could create my mask.

Enter Dirk'sLineNormals2D.

N = LineNormals2D(xsys);%Dirk-Jan!!!! This rocks!thicknessMultiplier = 2; posn = [xs-thicknessMultiplier*N(:,1) ys-thicknessMultiplier*N(:,2); flipud(xs+thicknessMultiplier*N(:,1)) flipud(ys+thicknessMultiplier*N(:,2))]; h = impoly(ax(2),posn); xsys = getPosition(h); xs = xsys(:,1); ys = xsys(:,2); plot(ax(1),xs,ys,'g.','markersize',16);

Now...

imshow(createMask(h),'parent',ax(2)) title('That''s more like it!')

The line above, in which I used the output ofLineNormals2Dto create my "posn" vector, might seem a bit puzzling. In a nutshell, Dirk-Jan's function calculated the position of thenormalat each point on myimroi. I subtract those values from, and then add them to, the points on my curve to calculate desired positions. (thicknessMultiplier just scales the amount of offset.) I useflipudto have the "inward points" flip around and start where the "outward points" left off:

t = 0:pi/64:3*pi; xy = [t',sin(t)']; N = LineNormals2D(xy); plot(xy(:,1),xy(:,2),“b”。) plot(xy(:,1)-N(:,1),xy(:,2)-N(:,2),'r.') plot(xy(:,1)+N(:,1),xy(:,2)+N(:,2),'g.') legend({'Original points','XY-N','XY+N'}) xlabel('t') ylabel(“罪(t)”)

Zooming in, we can see what LineNormals2D did more explicitly:

h = impoly(ax(2),posn); setColor(h,[1 0 1]) ax.xlim set(ax,'xlim',[165 230],'ylim',[1120 1200])

There are undoubtedly other ways of creating this mask, but this is what initially occurred to me. Swag, of course, goes to Dirk-Jan for his fine code, but also to anyone who shows me another clever way to implement this functionality!

As always, I welcome yourthoughts and comments.

Get the MATLAB code

Published with MATLAB® R2015a