Face Recognition


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

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.






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