public string Recognise(Image Input_image, int Eigen_Thresh = -1)įaceRecognizer.PredictionResult ER = recognizer.Predict(Input_image) It's always depend your data whatever training or test sets images.Īnd I read some article and I develop it. Actually there is no ideal threshold values such as system. With changing these threshold values, you can find most suitable values for your data. When I check your code I think these threshold values is so high. 'Image Input_image' this format is Emgu.CV format.

If ( result.Label = resultFish.Label = LBPresult.Label) If (result.Label != -1 & resultFish.Label != -1 & LBPresult.Label != -1) Var LBPresult = LBPeigenFaceRecognizer.Predict(_grayFrame) Var resultFish = FisheigenFaceRecognizer.Predict(_grayFrame) Var result = eigenFaceRecognizer.Predict(_grayFrame) LBPeigenFaceRecognizer = new LBPHFaceRecognizer(4, 8, 8, 8, 5000) eigenFaceRecognizer = new EigenFaceRecognizer(4,5000) įisheigenFaceRecognizer = new FisherFaceRecognizer(4, 5000) It gives 80-90% accuracy for the faces which are already present in the database, but for the unknown face which not present in the database, it always returns the best match face from the database. I have used a combination of three algorithms(EIGEN, FISHER & LBPH) to get better accuracy in face recognition. The issue is system always returns nearest matching face from the database for the unknown face. I'm working on face recognition system where I'm facing issue in detecting unknown faces.

C# opencv face detection