ThresholdImage_HSx


Transforms each pixel value to minimum or maximum depending on whether it belongs to specified region in the HSV, HSL or HSI color space.

Applications:Color analysis.

Syntax

C++
Python
 
def ThresholdImage_HSx(
	inRgbImage: Image,
	inBeginHue: int,
	inEndHue: int,
	outMonoImage: Image,
	/,
	*,
	inRoi: Region | None = None,
	inColorModel: HSxColorModel = HSxColorModel.HSV,
	inMinSaturation: int | None = 128,
	inMaxSaturation: int | None = None,
	inMinBrightness: int | None = 128,
	inMaxBrightness: int | None = None,
	inFuzziness: float = 0,
	diagHSxImage: Image | None = None
)
-> None

Parameters

Name Type Range Default Description
Input value inRgbImage Image Input image in the RGB color space
Input value inRoi Region | None None Region of interest
Input value inColorModel HSxColorModel HSxColorModel.HSV Selected color model
Input value inBeginHue int 0 - 255 Lowest acceptable Hue; if higher than inEndHue, then range wrapping is used
Input value inEndHue int 0 - 255 Highest acceptable Hue, if lower than inBeginHue, then range wrapping is used
Input value inMinSaturation int | None 0 - 255 128
Input value inMaxSaturation int | None 0 - 255 None
Input value inMinBrightness int | None 0 - 255 128 Minimum brightness; denotes V, L or I, depending on inColorModel
Input value inMaxBrightness int | None 0 - 255 None Maximum brightness; denotes V, L or I, depending on inColorModel
Input value inFuzziness float 0.0 - 0 Tolerance for value ranges that results in intermediate output values
Output value outMonoImage Image
Diagnostic input diagHSxImage Image | None None Image in HSx color space

Hardware Acceleration

This operation supports automatic parallelization for multicore and multiprocessor systems.