Minimum distance between the contour pixels of two regions each.
The operator distance_rr_min calculates the minimum distance of pairs of regions. If several regions are passed in Regions1 and Regions2 the distance between the contour pixels of each i-th element is calculated and then forms the i-th entry in the output parameter MinDistance. The calculation is carried out by comparing all contour pixels. The Euclidean distance is used. The parameters (Row1,Column1) and (Row2, Column2) indicate the position on the contour of Regions1 and Regions2, respectively, the distance between which is the minimum distance.
Each region must consist of exactly one connection component. Both input parameters must contain the same number of regions. The regions must not be empty. If the regions overlap the distance is indicated as 0.0. In this case the positions are not reliable.
|
Regions1 (input_object) |
region(-array) -> object |
| Regions to be examined. | |
|
Regions2 (input_object) |
region(-array) -> object |
| Regions to be examined. | |
|
MinDistance (output_control) |
real(-array) -> real |
| Minimum distance between contours of the regions. | |
| Assertion: 0 <= MinDistance | |
|
Row1 (output_control) |
point.y(-array) -> integer |
| Line index on contour in Regions1. | |
|
Column1 (output_control) |
point.x(-array) -> integer |
| Column index on contour in Regions1. | |
|
Row2 (output_control) |
point.y(-array) -> integer |
| Line index on contour in Regions2. | |
|
Column2 (output_control) |
point.x(-array) -> integer |
| Column index on contour in Regions2. | |
If N1,N2 are the lengths of the contours the runtime complexity is O(N1 * N2).
The operator distance_rr_min returns the value 2 (H_MSG_TRUE) if the input is not empty. Otherwise an exception handling is raised.
distance_rr_min is reentrant and automatically parallelized (on tuple level).
threshold, regiongrowing, connection
distance_rr_min_dil, dilation1, intersection
Region processing
