Create an object recognizer using the specific tranning data and parameters, it will always return the most similar object
Namespace:
Emgu.CVAssembly: Emgu.CV (in Emgu.CV.dll) Version: 2.0.1.0 (2.0.1.0)
Syntax
| C# |
|---|
public EigenObjectRecognizer( Image<Gray, byte>[] images, string[] labels, ref MCvTermCriteria termCrit ) |
| Visual Basic (Declaration) |
|---|
Public Sub New ( _ images As Image(Of Gray, Byte)(), _ labels As String(), _ ByRef termCrit As MCvTermCriteria _ ) |
| Visual C++ |
|---|
public: EigenObjectRecognizer( array<Image<Gray, unsigned char>^>^ images, array<String^>^ labels, MCvTermCriteria% termCrit ) |
Parameters
- images
- Type: array<
Emgu.CV..::.Image<(Of <(Gray, Byte>)>)
>[]()[]
The images used for training, each of them should be the same size. It's recommended the images are histogram normalized
- labels
- Type: array<
System..::.String
>[]()[]
The labels corresponding to the images
- termCrit
- Type:
Emgu.CV.Structure..::.MCvTermCriteria
%
The criteria for recognizer training