Face recognition help you to matching a human face from an image.
- Recognize face(s) in all orientations
- Automatically detect and crop face(s) in the image
The following is a list of conditions that can reduce performance of the model to recognize face.
- Blurry image
- Noisy image
- Poorly lightning condition or light reflection (often flashlight)
- Partially hidden or obstructed faces
Kredibel is using deep learning to perform face recognition task. Our model achieve near 99.7% accuracy in the labeled face in the wild (LFW) dataset. Below is an explanation of how our Face Detection system works.
Users can upload a handheld or non-handheld identity card image. Our system can handle both.
Our system will estimate image orientation and normalize it. That's why our system can recognize faces in all orientations.
Our system will detect all face(s) in the image.
Our system will automatically crop the face area detected by face detection model.
Our system will recognize face(s) by extracting face unique features.
We compare face unique features of the given image.