org.opencv.face

Class MACE

java.lang.Object

org.opencv.core.Algorithm

org.opencv.face.MACE

public class MACE
extends Algorithm

Minimum Average Correlation Energy Filter useful for authentication with (cancellable) biometrical features. (does not need many positives to train (10-50), and no negatives at all, also robust to noise/salting) see also: CITE: Savvides04 this implementation is largely based on: https://code.google.com/archive/p/pam-face-authentication (GSOC 2009) use it like: Ptr<face::MACE> mace = face::MACE::create(64); vector<Mat> pos_images = ... mace->train(pos_images); Mat query = ... bool same = mace->same(query); you can also use two-factor authentication, with an additional passphrase: String owners_passphrase = "ilikehotdogs"; Ptr<face::MACE> mace = face::MACE::create(64); mace->salt(owners_passphrase); vector<Mat> pos_images = ... mace->train(pos_images); // now, users have to give a valid passphrase, along with the image: Mat query = ... cout << "enter passphrase: "; string pass; getline(cin, pass); mace->salt(pass); bool same = mace->same(query); save/load your model: Ptr<face::MACE> mace = face::MACE::create(64); mace->train(pos_images); mace->save("my_mace.xml"); // later: Ptr<MACE> reloaded = MACE::load("my_mace.xml"); reloaded->same(some_image);

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	MACE(long addr)

Method Summary

Modifier and Type	Method and Description
static MACE	__fromPtr__(long addr)
static MACE	create() constructor
static MACE	create(int IMGSIZE) constructor
protected void	finalize()
static MACE	load(String filename) constructor
static MACE	load(String filename, String objname) constructor
void	salt(String passphrase) optionally encrypt images with random convolution
boolean	same(Mat query) correlate query img and threshold to min class value
void	train(List<Mat> images) train it on positive features compute the mace filter: h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C also calculate a minimal threshold for this class, the smallest self-similarity from the train images

Methods inherited from class org.opencv.core.Algorithm

clear, empty, getDefaultName, getNativeObjAddr, save

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

MACE

protected MACE(long addr)

Method Detail

__fromPtr__

public static MACE __fromPtr__(long addr)

create

public static MACE create(int IMGSIZE)

constructor

Parameters:

IMGSIZE - images will get resized to this (should be an even number)

Returns:

automatically generated

create

public static MACE create()

constructor

Returns:

automatically generated

load

public static MACE load(String filename,
                        String objname)

constructor

Parameters:

filename - build a new MACE instance from a pre-serialized FileStorage

objname - (optional) top-level node in the FileStorage

Returns:

automatically generated

load

public static MACE load(String filename)

constructor

Parameters:

filename - build a new MACE instance from a pre-serialized FileStorage

Returns:

automatically generated

same

public boolean same(Mat query)

correlate query img and threshold to min class value

Parameters:

query - a Mat with query image

Returns:

automatically generated

salt

public void salt(String passphrase)

optionally encrypt images with random convolution

Parameters:

passphrase - a crc64 random seed will get generated from this

train

public void train(List<Mat> images)

train it on positive features compute the mace filter: h = D(-1) * X * (X(+) * D(-1) * X)(-1) * C also calculate a minimal threshold for this class, the smallest self-similarity from the train images

Parameters:

images - a vector<Mat> with the train images

finalize

protected void finalize()
                 throws Throwable

Overrides:

finalize in class Algorithm

Throws:

Throwable