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Some papers use image segmentation techniques and others use edge detection. I need to know which one is faster.

update:

I need to do semantic segmentation for outdoor sense and the data is optical image and LiDAR. Other researchers use segmentation before doing feature detection but I expect that if I use line/edge detection, the technique will detect image features faster.

Before I start doing experiments I want to know which one is better because this will effect on next step, i.e. feature detect.

This application should work in real-time and I plan to use GPU for faster processing, such as CUDA.

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  • $\begingroup$ Welcome to SP.SE! Your question is very, very general and not clear. You need to provide much more information: what sort of images are you using? What is the application that you need edge detection / segmentation for? What have you tried? How fast do you need it? Closing until we get some more details. $\endgroup$
    – Peter K.
    Oct 13, 2016 at 16:54
  • $\begingroup$ @peterK. I add all info you ask for $\endgroup$ Oct 17, 2016 at 0:30

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Image segmentation is way harder and more complex than a local operation like edge detection. You may do things in parallel for edge detection as one does not interfere with the other. Global segmentation can't allow this.

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