FindMaxStableExtremalRegions


Segments an image by binarizing it with many different thresholds and by looking which blobs appear "stable".

Applications:Most frequently used for finding correspondence points between two images.

Syntax

C++
C#
Python
 
def FindMaxStableExtremalRegions(
	inImage: Image,
	/,
	*,
	inDelta: int = 30,
	inMinArea: int = 50,
	inMaxArea: int = 2000,
	inMaxVariation: float = 0.1,
	inMinDiversity: float = 2.0,
	inConnectivity: RegionConnectivity = RegionConnectivity.EightDirections
)
-> outRegions: list[Region]

Parameters

Name Type Range Default Description
Input value inImage Image Input image
Input value inDelta int 1 - 255 30 Area variance is calculated against ancestor with color difference of delta
Input value inMinArea int 0 - 50 Minimum area of stable region
Input value inMaxArea int 0 - 2000 Maximum area of stable region
Input value inMaxVariation float 0.0 - 0.1 Maximum area variance with containing larger region specified by delta parameter, for region to be considered as stable
Input value inMinDiversity float 0.0 - 2.0 Minimum area diversity that region must have in order to be stable when compared to stable regions within it
Input value inConnectivity RegionConnectivity RegionConnectivity.EightDirections
Output value outRegions list[Region]