Segments a color image using trained samples.
Cluster of parameters used to configure the color segmentation algorithm.
Cluster specifying the size of the window the node uses when calculating the color segmentation.
Window size in x direction.
Window size in y direction.
Distance between two windows.
Minimum number of allowed pixels.
Any particle with fewer pixels than this parameter will be deleted.
Maximum number of allowed pixels.
Any particle with fewer pixels than this parameter will be deleted.
Boolean that, when enabled, processes the boundary pixels of each segmentation cluster using a step size of 1.
Enabling this parameter increases the time required to process the image, but also increases segmentation accuracy.
TRUE | Processes the boundary pixels of each segmentation cluster. |
FALSE | Does not process the boundary pixels. |
Region of interest specifying the location of the sample in the image.
The ROI must be one or more closed contours. If ROI descriptor is empty or not connected, the entire image is considered to be the region. For best performance, use only one rectangle or one rotated rectangle per sample.
Coordinates of the bounding rectangle.
Individual shapes that define an ROI.
Object specifying if contour is the external or internal edge of an ROI.
Shape type of the contour.
Relative position of the contour.
Reference to the classifier session on which this node operates.
Reference to the color image to segment based on color information.
Reference to the image to store labels of segmented color image.
The label image must be one of the following image data types: U8, U16, or I16.
Array of class names and labels to be segmented.
Pass an empty array if all the trained classes are required.
Class you want to segment.
Label number associated with class name.
Error conditions that occur before this node runs.
The node responds to this input according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Default: No error
Minimum identification score required to group the pixel.
Valid values are 0 to 1000.
Maximum allowed color distance to group the pixel windows.
Valid values are 0 to 1000. A value of 0 represents a conservative search strategy and a value of 1000 represents an aggressive search strategy.
Reference to the session referenced by classifier session in.
Reference to the source image.
Reference to the image with stored labels of segmented color image.
Array of class names and label numbers that correspond with the labels of the label image.
One of the segmented classes.
Label number associated with the class name.
Error information.
The node produces this output according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Where This Node Can Run:
Desktop OS: Windows
FPGA: Not supported
Web Server: Not supported in VIs that run in a web application