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Masking
Usage
Processes
Convert binary mask to contouring mask
Converts a binary mask to a contouring mask with the values of the input binary mask as its first layer.
Create soft mask from image
Creates a soft mask from a 3D input. First, the map is binarized a the given threshold. Second, the binary mask is expanded by the kernel radius. Now, an additional soft transition is added to the mask resulting in the final softmask.
| Parameters | Description |
|---|---|
| Kernel radius | Number of pixel added to the binarized mask for expansion. |
| Min segment size [%] | Percentage of total volume that needs to be enclosed by the mask. This helps to create the mask only for large volumes/maps while excluding small dirt particles. |
| Soft kernel radius | Additionally to the kernel, a soft transition is added to the mask to prevent sharp edges. |
| Threshold | Initial threshold of map where binarization is applied. |
Invert mask
Each pixel value of every image is inverted with respect to the value spectrum of all pixels. If the image value spectrum ranges from 0 to 1, a pixel with value 1 will become 0 and vise versa.
Soft circle
| Parameters | Description |
|---|---|
| Threshold for binarization | Description of this parameter |
Concept
In this paragraph, the “HOW a logic works under the hood” and WHY someone should use it can be elaborated with higher detail. Describes a scenario in an image processing workflow where this logic can be used to solve the resulting problem. Also, wikipages, publications or anything else describing the theory behind an algorithm should be linked here, if applicable.