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

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

Create an object recognizer using the specific tranning data and parameters

Caculate the eigen images for the specific traning image

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

Given the eigen value, reconstruct the projected image

Determines whether the specified Object is equal to the current Object.

Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.

Given the image to be examined, find in the database the most similar object, return the index and the eigen distance

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

Serves as a hash function for a particular type.

Gets the Type of the current instance.

Creates a shallow copy of the current Object.

Try to recognize the image and return its label

Returns a String that represents the current Object.

Get the average Image.

Get or set the eigen distance threshold. The smaller the number, the more likely an examined image will be treated as unrecognized object. Set it to a huge number (e.g. 5000) and the recognizer will always treated the examined image as one of the known object.

Get the eigen vectors that form the eigen space

Get the eigen values of each of the training image

Get or set the labels for the corresponding training image