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eyes:logics:morphologicaloperations [2017/06/07 16:19] jschlie1 created |
eyes:logics:morphologicaloperations [2017/06/08 15:44] (current) jschlie1 |
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| - | ====== morphologicalOperations ====== | + | ====== MorphologicalOperations ====== |
| ===== Usage ===== | ===== Usage ===== | ||
| This logic applies mathematical morphology operators onto the data. As input, a (stack of) binary or grayscale image(s) is possible. The respecitve effect of each operator is described below. | This logic applies mathematical morphology operators onto the data. As input, a (stack of) binary or grayscale image(s) is possible. The respecitve effect of each operator is described below. | ||
| - | |||
| - | ===== Example ==== | ||
| - | Here, a very specific example should be given/described. In the future, this can be supported by screenshots etc.. For the moment, give an example easy enough for the user to understand, but specific enough to elaborate why a given parameter is a good set for this very situation. | ||
| ===== Operators ===== | ===== Operators ===== | ||
| ==== Closing ==== | ==== Closing ==== | ||
| + | FIXME | ||
| ==== Dilation ==== | ==== Dilation ==== | ||
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| Erosion performs the mathematical morphology operator called Erosion. It must be applied to a binary or grayscale image. Its basic effect is to shrink boundaries of regions of foreground pixels (1's). Thus areas of foreground pixels shrink in size and wholes within those regions grow. | Erosion performs the mathematical morphology operator called Erosion. It must be applied to a binary or grayscale image. Its basic effect is to shrink boundaries of regions of foreground pixels (1's). Thus areas of foreground pixels shrink in size and wholes within those regions grow. | ||
| - | ==== Erosion ==== | + | ==== Opening ==== |
| + | FIXME | ||
| + | |||
| + | ==== Skeletonization ==== | ||
| + | FIXME | ||
| + | |||
| + | ===== Parameters and I/O ===== | ||
| |< 100% 30% >| | |< 100% 30% >| | ||
| - | ^ Parameters ^ Description ^ | + | ^ Parameters ^ Description ^ |
| | Input image format | This value can either be set to binary or grayscale. Choose according to the input data format. | | | Input image format | This value can either be set to binary or grayscale. Choose according to the input data format. | | ||
| | binary | Sets the input format to binary (only 0 and 1 as values). | | | binary | Sets the input format to binary (only 0 and 1 as values). | | ||
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| | output | Images after application of the operation. | | | output | Images after application of the operation. | | ||
| - | ===== 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. | ||