Hi,
I am new to active shape models (ASM) and I want to use it in my research to do image segmentation.
For using ASM, there should be a training set to generate the shape statistical model: x = xbar+Pb, where xbaris the mean shape and P is the eigenvectors, x is the shapes obtained by changing the shape parameters b.
In my particular case, there is no training set. However, the mean shape is known, so is the shape constraints. Is there a way to use the statistical model? Use simulated shapes for training? But how to mimic the gray-level profile?
Thanks in advance.
Dear Sir,
I am sorry that I don't know how do it. Thank you for asking me. Good luck to you.
Just attach the image files with the "paper clip" below the message...
you can simulate around the mean, depending on your model (i.e. draw samples from your distribution), in your case, change the 'b' value (and others if any) to generate different shapes, but these would just be linear combinations of the eigenvectors. you can also try some non linear transforms (specially since these are deformable shapes) and keep those samples which satisfy the constraints.
- Badges
- Science topic
- Similar topics
- Biological Science
- Physiology
- Biosignals
- Biomedical Signal Processing