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AVL.CompareGoldenTemplate_Intensity

Compares an image with a template image considered to have no defects.

Namespace:AvlNet
Assembly:AVL.NET.dll

Syntax

C++
C#
 
public static void CompareGoldenTemplate_Intensity
(
	AvlNet.Image inImage,
	AvlNet.GrayGoldenTemplate inGoldenTemplate,
	AvlNet.CoordinateSystem2D? inGoldenTemplateAlignment,
	float inMaxDifference,
	int inMinDefectRadius,
	AvlNet.Region outDefects,
	AvlNet.Region outDifferenceRegion,
	out bool outDefectsPresent,
	AvlNet.Region outEdgeRegion
)

Parameters

Name Type Range Default Description
inImageAvlNet.ImageInput image.
inGoldenTemplateAvlNet.GrayGoldenTemplateGolden gray template containing image of an object with no defects.
inGoldenTemplateAlignmentAvlNet.CoordinateSystem2D?Adjusts the golden template to the position of the inspected object. Default value: atl::NIL.
inMaxDifferencefloat<0.0f, INF>20.0fMaximal allowed difference between corresponding pixels of the input and golden images. Default value: 20.0f.
inMinDefectRadiusint<0, INF>1Minimal radius of a defect. Default value: 1.
outDefectsAvlNet.RegionRegion of detected defects.
outDifferenceRegionAvlNet.RegionRegion of pixels differing too much between the golden image and the input image.
outDefectsPresentboolFlag indicating whether any defects were detected.
outEdgeRegionAvlNet.RegionRegion of pixels that will not be compared.

Description

This filter compares pixels of the input images against a template image stored in passed inGoldenTemplate input. Then creates a region containing only pixels in which intensity difference is higher than inMaxDifference value as a result. This method is especially useful for finding defects like: smudges, noises and dust particles. It can be used for finding missing holes or changes in complex shapes.

When the defected pixels are found only consistent regions are selected. Minimal radius of accepted region is set in inMinDefectRadius.

You can define a part of an image when defining inGoldenTemplate.

More information about this technique can be found in Machine Vision Guide: Golden Template.

Examples

CompareGoldenTemplate_Intensity performed on sample image. A part of the object is missing – it is marked in blue on the right.

Remarks

Due to performance, it is recommended to create a template using the CreateGoldenTemplate_Intensity filter outside a main loop of a program. It will create a model only once, instead of each iteration.

Errors

List of possible exceptions:

Error type Description
DomainError Input image format is incompatible with golden template image format in CompareGoldenTemplate_Intensity.
DomainError No valid golden template on input in CompareGoldenTemplate_Intensity.

Function Overrides

See also