How do I confine this code (http://www.mathworks.com/help/vision/examples/motion-based-multiple-object-tracking.html) to happen only inside the ROI.
Similar to this one wherein a visible rectangle is specified and any vehicles that enter it are the only ones that are processed:
(Source: https://www.youtube.com/watch?v=IPmG30byCyc)
https://uk.mathworks.com/help/images/ref/roipoly.html
As stated here, define your region, create a binary mask and mask your original image with it, as to only leave a region of interest.
Related
For Example, I have the below image used for demo purpose only
Fill close portion with pattern
if user tap on any part of T-Shirt, than T-Shirt should be filled with selected pattern image.
I have used to find an array of the point contains close area it takes time as well to find close region points and try to draw color at that points, but it takes too much time to draw because there are many points for the close region.
I have used code from below link
https://github.com/Chintan-Dave/UIImageScanlineFloodfill
This algorithm is actually for flood fill, but I have added one more method to collect all points to one NSSet.
A help is too much appreciated.
Thanks in advance.
I have processed an image to the point where I have certain labelled regions. Shown here with each labelled region in different shade.
I would like to show the outline of each region separately. Currently I am using bwmorph(labeledImage,'remove') but this treats any regions contacting each other and keeps the outlines of the conjunction of the multiple regions.
I am looking for a function that will keep all the outline / edge pixels for each region, something that would result in an image like the following (green edges added to show what is missing from the method I am already using).
You can differentiate all regions, so why dont you treat them separatly?
See this bwboundaries.
I have already tried imfill(img) but that doesn't work at all.
I have noticed that imfill works for this purpose only for images in which the object's boundary is complete and not broken like the image i am taking .
For this particular image do the following:
Prepend a white row to the image to close the contour.
Fill the contour.
Remove the helper row.
Anything else requires more information and examples.
Matlab documentation states that "a hole is a set of background pixels that cannot be reached by filling in the background from the edge of the image". In this case any pixel can be reached from the edge because its boundary is not complete. Therefore, technically there is no hole in the image you posted.
I have an ellipse in the image.After segmentation i got a broken ellipse as shown .which morphological operation is used to get the perfect ellipse
Actual input file is
output obtained is
i tried imopen ,but i will lose lower ellipse like structure .how to close the upper ellipse like structure without losing lower ones
Mask i created is
i want to segment the ellipse like structure.but some of these structures are connected with rectangular like bodies.how to separate it. erode will eliminate small ellipses
If you want to reconnect something with a mathematical morphology operator, do not use an opening (it increases the gap), but a closing (imclose)! The names are explicits.
In you case, you want to reconnect something vertically cut, so use a horizontal structuring element (type segment).
And yes, you have to invert your image, black pixels representing the absence of information.
Usually, for closing gaps, you would need the close operator.
However, since most software assume active pixels are white, you would either need to invert the image, or use the open operator.
On this image, in matlab, the following works well:
imopen(I,ones(32))
This uses a square structuring element. You may want to experiment with other shapes.
Your example also looks like you moved half of the ellipse, as opposed to some process which deleted pixels in the middle. No simple morphological operation can create a perfect ellipse out of the sample image, unless you use the knowledge that multiple components can be moved to re-form the ellipse. If that is the actual case, you can scan connected components and try to match them together.
I'd like to resize the components contained in a 3D binary image sequence without changing any of the dimensions of the sequence itself.
I'm not sure if I need to do it on a component-by-component basis, if yes, then how do I create a transform such that the resized components are re-positioned 'correctly' in the image sequence? By 'correctly', I mean with the same centre of mass as the original unprocessed components.
(If that last paragraph doesn't make sense then please ignore)
A 2D example: suppose I wanted to enlarge by 10% the white blobs in the following [295x445] image
How would you do this without making the image itself larger?
you could use the imdilate function to dilate the regions of interest. The examples in the webpage show how to use this function.