Supervised Color Segmentation (G Dataflow)

Cluster of parameters used to configure the color segmentation algorithm.

window size

Cluster specifying the size of the window the node uses when calculating the color segmentation.

x

Window size in x direction.

y

Window size in y direction.

step size

Distance between two windows.

min particle area

Minimum number of allowed pixels.

Any particle with fewer pixels than this parameter will be deleted.

max particle area

Maximum number of allowed pixels.

Any particle with fewer pixels than this parameter will be deleted.

refine segmentation?

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.

Global Rectangle

Coordinates of the bounding rectangle.

Contours

Individual shapes that define an ROI.

ID

Object specifying if contour is the external or internal edge of an ROI.

Type

Shape type of the contour.

Coordinates

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 name

Class you want to segment.

label

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.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

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.

class name

One of the segmented classes.

label

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.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.