ThresholdImage
Transforms each pixel value to maximum or minimum depending on whether they belong to the specified range.
Applications:Image binarization when the illumination is constant and uniform.
Syntax
C++
Python
def ThresholdImage( inImage: Image, outMonoImage: Image, /, *, inRoi: Region | None = None, inMinValue: float | None = 128.0, inMaxValue: float | None = None, inFuzziness: float = 0.0 ) -> None
Parameters
| Name | Type | Range | Default | Description | |
|---|---|---|---|---|---|
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inImage | Image | Input image | ||
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inRoi | Region | None | None | Region of interest | |
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inMinValue | float | None | 128.0 | Minimum value of a pixel that is considered foreground (Auto = -INF) | |
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inMaxValue | float | None | None | Maximum value of a pixel that is considered foreground (Auto = +INF) | |
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inFuzziness | float | 0.0 - ![]() |
0.0 | A tolerance for inMin/MaxValue that results in intermediate output values |
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outMonoImage | Image |
Hardware Acceleration
This operation is optimized for SSE2 technology for pixels of types: 1xUINT8 (for inFuzziness = 0), 3xUINT8 (for inFuzziness = 0).
This operation is optimized for AVX2 technology for pixels of types: 1xUINT8 (for inFuzziness = 0), 3xUINT8 (for inFuzziness = 0).
This operation is optimized for NEON technology for pixels of types: 1xUINT8 (for inFuzziness = 0), 3xUINT8 (for inFuzziness = 0).
This operation supports automatic parallelization for multicore and multiprocessor systems.



