C# 클래스 Emgu.CV.EigenObjectRecognizer

공개 메소드들

메소드	설명
CalcEigenObjects ( Byte>.Image trainingImages, MCvTermCriteria &termCrit, Single>.Image &eigenImages, Single>.Image &avg ) : void	Caculate the eigen images for the specific traning image
EigenDecomposite ( Byte>.Image src, Single>.Image eigenImages, Single>.Image avg ) : float[]	Decompose the image as eigen values, using the specific eigen vectors
EigenObjectRecognizer ( Byte>.Image images, MCvTermCriteria &termCrit ) : System	Create an object recognizer using the specific tranning data and parameters, it will always return the most similar object
EigenObjectRecognizer ( Byte>.Image images, String labels, MCvTermCriteria &termCrit ) : System	Create an object recognizer using the specific tranning data and parameters, it will always return the most similar object
EigenObjectRecognizer ( Byte>.Image images, String labels, double eigenDistanceThreshold, MCvTermCriteria &termCrit ) : System	Create an object recognizer using the specific tranning data and parameters
EigenProjection ( float eigenValue ) : Byte>.Image	Given the eigen value, reconstruct the projected image
GetEigenDistances ( Byte>.Image image ) : float[]	Get the Euclidean eigen-distance between image and every other image in the database
Recognize ( Byte>.Image image ) : RecognitionResult	Try to recognize the image and return its label

메소드	설명
EigenObjectRecognizer ( ) : System
GenerateLabels ( int size ) : String[]

Caculate the eigen images for the specific traning image

public static CalcEigenObjects ( Byte>.Image trainingImages, MCvTermCriteria &termCrit, Single>.Image &eigenImages, Single>.Image &avg ) : void
trainingImages	Byte>.Image	The images used for training
termCrit	Emgu.CV.Structure.MCvTermCriteria	The criteria for tranning
eigenImages	Single>.Image	The resulting eigen images
avg	Single>.Image	The resulting average image
리턴	void

Decompose the image as eigen values, using the specific eigen vectors

public static EigenDecomposite ( Byte>.Image src, Single>.Image eigenImages, Single>.Image avg ) : float[]
src	Byte>.Image	The image to be decomposed
eigenImages	Single>.Image	The eigen images
avg	Single>.Image	The average images
리턴	float[]

Create an object recognizer using the specific tranning data and parameters, it will always return the most similar object

public EigenObjectRecognizer ( Byte>.Image images, MCvTermCriteria &termCrit ) : System
images	Byte>.Image	The images used for training, each of them should be the same size. It's recommended the images are histogram normalized
termCrit	Emgu.CV.Structure.MCvTermCriteria	The criteria for recognizer training
리턴	System

Create an object recognizer using the specific tranning data and parameters, it will always return the most similar object

public EigenObjectRecognizer ( Byte>.Image images, String labels, MCvTermCriteria &termCrit ) : System
images	Byte>.Image	The images used for training, each of them should be the same size. It's recommended the images are histogram normalized
labels	String	The labels corresponding to the images
termCrit	Emgu.CV.Structure.MCvTermCriteria	The criteria for recognizer training
리턴	System

Create an object recognizer using the specific tranning data and parameters

public EigenObjectRecognizer ( Byte>.Image images, String labels, double eigenDistanceThreshold, MCvTermCriteria &termCrit ) : System
images	Byte>.Image	The images used for training, each of them should be the same size. It's recommended the images are histogram normalized
labels	String	The labels corresponding to the images
eigenDistanceThreshold	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	Emgu.CV.Structure.MCvTermCriteria	The criteria for recognizer training
리턴	System

Given the eigen value, reconstruct the projected image

public EigenProjection ( float eigenValue ) : Byte>.Image
eigenValue	float	The eigen values
리턴	Byte>.Image

Get the Euclidean eigen-distance between image and every other image in the database

public GetEigenDistances ( Byte>.Image image ) : float[]
image	Byte>.Image	The image to be compared from the training images
리턴	float[]

Try to recognize the image and return its label

public Recognize ( Byte>.Image image ) : RecognitionResult
image	Byte>.Image	The image to be recognized
리턴	RecognitionResult