I have set of point clouds, representing boundaries of different closed polygons. These polygons contains 3d points. But they also can be considered as a 2d case once boundary points are projected to the xy plane. Though these boundaries are irregular, it can be fitted into small, straight line segments. I am trying to do this fitting by least square method. But, before that, I want to identify the turning points or the corresponding point sets for each straight line segment which I am going to fit. So, I am looking for a good, fast method. I know that the dougles-peuker algorithm could be used to reduce the points along the boundary and then to identify the turning points. But, I feel it would not be giving me major turning spots like 20, 45, 90, degrees... turnings of the boundary.
- if anyone can point out a robust method to find major turning points along the boundary it is highly grateful.
- also, please tell me, how can i combine dougles-peuker algorithm and least square
fitting to get straight line segments together with available turns (if any) like
20,45,90,..degrees in between consecutive line segments.
- may be, one can give me some other methods or if can give me some related papers which is able to detect turning points of the point boundaries.
- actually i am looking for point generalization algorithm which is able to keep turning points.