Face Recognition
Introduction
Face recognition help you to matching a human face from an image.
Ability
Recognize face(s) in all orientations
Automatically detect and crop face(s) in the image
Limitations
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
Under the Hood
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.
1. Upload Image
Users can upload a handheld or non-handheld identity card image. Our system can handle both.
2. Orientation estimation
Our system will estimate image orientation and normalize it. That's why our system can recognize faces in all orientations.
3. Face Detection
Our system will detect all face(s) in the image.
4. Cropping
Our system will automatically crop the face area detected by face detection model.
5. Face Recognition
Our system will recognize face(s) by extracting face unique features.
6. Face Comparison
We compare face unique features of the given image.
Endpoints
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