In the computer vision literature, this approach is referred to
Difference of Gaussians (DoG) approach. Besides minor
however, this operator is in essence similar to the
Laplacian and can
be seen as an approximation of the Laplacian
operator. In a similar
fashion as for the Laplacian blob detector,
blobs can be detected
from scale-space extrema of differences of
Select whether you want to detect minima or
Threshold value for detected extrema. Maxima below or minima above the value will be disregarded.
Whether the peak value should be normalized. If this option is checked, the DoG will be scaled by Sigma1 / (Sigma2 - Sigma1).
Sigma for the smaller scale
Sigma for the larger scale
Out of Bounds Strategy
The 'OutOfBounds Strategy' is used when an algorithm needs access to
pixels which lie outside of an image (for example convolutions). The
strategy determines how an image is extended, for examples see
This component allows the selection of dimensions of interest.
If an algorithm cannot, as it only supports fewer dimensions than the number of dimensions of the image, or shouldnot, as one wants to run the algorithm only on subsets of the image, be applied on the complete image, the dimension selection can be used to define the plane/cube/hypercube on which the algorithm is applied.
Example 1 with three dimensional Image (X,Y,Time): An algorithm cannot be applied to the complete image, as it only supports two dimensional images. If you select e.g. X,Y then the algorithm will be applied to all X,Y planes individually.
Example 2 with three dimensional Image (X,Y,Time): The algorithm can be applied in two, three or even more dimensions. Select the dimensions to define your plane/cube/hypercube on which the algorithm will be applied.
Column Creation Mode
Mode how to handle the selected column. The processed column can be added to a new table, appended to the end of the table, or the old column can be replaced by the new result
A suffix appended to the column name. If "Append" is not selected, it can be left empty.
Selection of the columns to be processed.
BitType Images of Spots
Another, possibly interactive, view on table cells. Displays the selected cells with their associated viewer if it exists. Available views are: - Image Viewer -- This viewer renders the selected image-cell. - Combined View -- A viewer shown when the user selects an interval of rows and columns in the viewer. This viewer combines all images and labelings in the selected interval to one image by rendering them next to each other. Alternatively, the images and labelings can be layed over each other. - Missing Value Viewer -- An empty viewer that is shown when the input cell has no value to display. - XML -- XML tree - Histogram Viewer -- This viewer shows the histogram of the currently selected image. - Labeling View -- View on a labeling/segmentation
To use this node in KNIME, install KNIME Image Types and Nodes from the following update site:
Wait a sec! You want to explore and install nodes even faster? We highly recommend our
NodePit for KNIME
extension for your KNIME Analytics Platform.
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well?
Do you think, the search results could be improved or something is missing?
Then please get in touch! Alternatively, you can send us an email to email@example.com,
follow @NodePit on Twitter,
or chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.