Transform2DComposed.BestFitLinearTransform Method

Transform2DComposed BestFitLinearTransform Method

Cognex VisionPro 9.21 SR1

Returns a new linear transform which best describes this transform over the given set of points. The points must be expressed in 'from' coordinates.

Namespace: Cognex.Vision
Assembly: Cognex.Vision.Core.Net (in Cognex.Vision.Core.Net.dll) Version: 9.21.1.1

Syntax

C++

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public Transform2DLinear BestFitLinearTransform(
	Vect2Collection fromPoints,
	out double rmsError
)

public Transform2DLinear BestFitLinearTransform(
	Vect2Collection fromPoints,
	out double rmsError
)

Public Function BestFitLinearTransform ( 
	fromPoints As Vect2Collection,
	<OutAttribute> ByRef rmsError As Double
) As Transform2DLinear

Public Function BestFitLinearTransform ( 
	fromPoints As Vect2Collection,
	<OutAttribute> ByRef rmsError As Double
) As Transform2DLinear

public:
virtual Transform2DLinear^ BestFitLinearTransform(
	Vect2Collection^ fromPoints, 
	[OutAttribute] double% rmsError
) sealed

public:
virtual Transform2DLinear^ BestFitLinearTransform(
	Vect2Collection^ fromPoints, 
	[OutAttribute] double% rmsError
) sealed

Parameters

fromPoints: Type: Cognex.Vision Vect2Collection
A collection of points, expressed in From coordinates, for which to apply.

rmsError: Type: System Double
Sets it to the RMS error of the points against the returned linear transformation. A value of 0 indicates that the returned transformation exactly maps the points. Note that the RMS error is measured in To space. . is the Root Mean Square (RMS) unweighted Euclidian error between two sets of corresponding points. Set A is composed of the given points (in From space) after they have been mapped through this transform into To space. Set B is the same points after they have been mapped to To space using the linear transform returned by this function.

Return Value

Type: Transform2DLinear

Implements

ITransform2D BestFitLinearTransform(Vect2Collection, Double )

Exceptions

Exception	Condition
TransformException	Too few points were provided to compute a best fit linear transform.

Remarks

Returns a new linear transform that best describes this transform over the given set of points. These points must be expressed in From coordinates. The returned transform is called the "best-fit linear transform" because it is guaranteed to produce the smallest RMSError of any linear transform.