问题
In OpenCV, there are two methods of detecting lines that give similar results in the form of a vector of endpoints - the Line Segments Detector (LSD) and the Probabilistic Hough Transform. (Discounting the standard Hough transform as the output given is in terms of equations, not line endpoints.)
I haven't been able to find a compare and contrast of these two line detection methods and their pros/cons. Thus - what is the difference between these two functions? Are there any particular benefits to using one method as opposed to the other?
Additionally, are there other lesser-known line detection methods (like LSD) that might be advantageous in some use cases?
回答1:
Line Segments Detector (LSD)
- Takes a greyscale image as input
- Designed to work without any parameter tuning
- Runs in linear time
- Gives subpixel accurate results
- Useful for parameter-free edge detection
- LSD paper by Grompone Von Gioi et al
- Example implementation: using LSD to detect data matrices
(Progressive) Probabilistic Hough Transform
- Takes a binary image as input
- Has several tuning parameters; distance resolution (rho), angle resolution (theta), an accumulator threshold parameter (only those with enough votes are returned), minimum line length and maximum line gap
- Time performance depends on parameters (but is improved over standard Hough transform)
- Several runs may yield different results due to randomised nature
- Useful for more specific line finding; parameters allow for tuning, and has option to combine segments (via maximum line gap parameter) to return single longer lines
- The OpenCV implementation is the Progressive Probabilistic Hough Transform (with thanks to Dr. D.'s answer on this question)
Other algorithms
- EDLines: a linear time line segment detector that utilises an edge detector. No OpenCV implementation as far as I know.
(With thanks to Micka's comment for pointing out the differences in input and potential uses)
来源：https://stackoverflow.com/questions/43050075/line-segment-detector-vs-probabalistic-hough-transform