Color Processing

Owning Palette: Image Processing
Requires: NI Vision Development Module

Use the Color Processing VIs to perform basic processing on color images. Use these VIs to compute the histogram of a color image; apply lookup tables to color images; change the brightness, contrast, and gamma information associated with a color image; and threshold a color image.t

Palette Object Description
IMAQ ColorHistogram

Calculates the histograms extracted from the three planes of an image. This VI can function in one of six modes corresponding to the six color models (RGB, HSL, HSV, HSI, CIE L*a*b*, or CIE XYZ). The IMAQ ColorHistograph VI, a variant of the IMAQ ColorHistogram VI, has the advantage that its output data is directly compatible with a LabVIEW graph.

IMAQ ColorHistograph

Calculates the histograms extracted from the three planes of an image. This VI can function in one of four modes corresponding to the color models RGB, HSL, HSV, and HSI. The output from this VI is directly compatible with a LabVIEW graph.

IMAQ ColorUserLookup

Applies a lookup table (LUT) to each color plane.

IMAQ ColorBCGLookup

Applies a brightness, contrast, and gamma correction to each color plane separately.

IMAQ ColorEqualize

Equalizes a color image. This VI equalizes either the luminance plane (default) or all three planes.

IMAQ ColorThreshold

Applies a threshold to the three planes of an RGB or HSL image and places the result into an 8-bit image.

IMAQ Color Segmentation Supervised

Segments a color image using trained samples.

IMAQ Get Color Segmentation Distance

Gets the maximum distance allowed to group classes in color image segmentation.

IMAQ ColorLearn

Extracts the color features of an image, which can be used for color matching or other applications related with color information, such as color identification and color image segmentation.

IMAQ ColorMatch

Finds the match between the color content of multiple regions in an image and those defined by the input Color Spectrum.



Subpalette Description
Classification

Use Classification VIs to identify unknown objects by comparing significant features to a set of features that conceptually represent classes of known objects.

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