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Assembly: Emgu.CV (in Emgu.CV.dll) Version: 2.4.2.1777 (2.4.2.1777)
Create an object recognizer using the specific tranning data and parameters
Namespace: Emgu.CVAssembly: Emgu.CV (in Emgu.CV.dll) Version: 2.4.2.1777 (2.4.2.1777)
Syntax
C# |
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public EigenObjectRecognizer( Image<Gray, byte>[] images, string[] labels, double eigenDistanceThreshold, ref MCvTermCriteria termCrit ) |
Visual Basic |
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Public Sub New ( _ images As Image(Of Gray, Byte)(), _ labels As String(), _ eigenDistanceThreshold As Double, _ ByRef termCrit As MCvTermCriteria _ ) |
Visual C++ |
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public: EigenObjectRecognizer( array<Image<Gray, unsigned char>^>^ images, array<String^>^ labels, double eigenDistanceThreshold, 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
- eigenDistanceThreshold
- Type: System..::..Double
The eigen distance threshold, (0, ~1000]. The smaller the number, the more likely an examined image will be treated as unrecognized object. If the threshold is < 0, the recognizer will always treated the examined image as one of the known object.
- termCrit
- Type: Emgu.CV.Structure..::..MCvTermCriteria%
The criteria for recognizer training