1:1 Biometric Comparison

Face Match

The LumiID Face Match API provides a precise 1:1 biometric comparison between two images. Compare a live selfie against a stored ID photo to verify identity in milliseconds.

2-Minute Integration

Pass your API Key in the Authorization header.

Send two images (Base64 or URL) as source_image and target_image.

Receive a JSON response with a match_result and confidence_score.

Endpoint

POST /v1/face-match/

Body Parameters

Parameter	Type / Description
source_image Required	string (Base64 or URL) The "live" image captured from the user. Supports raw Base64 strings or publicly accessible image URLs.
target_image Required	string (Base64 or URL) The reference image (e.g., from a National ID or Passport). Used as the "truth" for comparison.
threshold Optional	float Acceptable range: `0.0` to `1.0`. Determines the strictness of the match. Default: 0.75

Common Use Cases

Face Matching is the definitive bridge between a digital claim and a physical human being. It turns a "passive" document into an active security key, essential for:

🏦

Secure Account Recovery

Eliminate the risk of social engineering. Verify a user's live face against the biometric data captured during registration before allowing password resets or change of phone numbers.

🛂

Digital KYC & Onboarding

Meet Tier 3 KYC requirements by ensuring the person holding the device is the legitimate owner of the uploaded NIN, Passport, or Driver's License.

💎

Step-up Authentication

Trigger a face match for high-risk actions, such as large fund transfers or modification of sensitive organizational settings, to prevent unauthorized access.

🛡️

Anti-Spoofing & Liveness

Combined with passive liveness detection, face matching prevents "presentation attacks" where fraudsters use high-res photos or videos to bypass security.

Why it matters for Compliance

Modern regulations (AML/CFT) increasingly require biometric binding. Face Matching provides an immutable audit trail, proving that a physical person was present and verified during a transaction, significantly reducing the liability of "ghost accounts" and identity theft.

Example Request

import requests
import json

url = "https://api.lumiid.com/v1/face-match/"

payload = json.dumps({
  "source_image": "base64_or_url_of_live_selfie",
  "target_image": "base64_or_url_of_id_card",
  "threshold": 0.75
})

headers = {
  'Authorization': 'Bearer Your-Secret-Key',
  'Content-Type': 'application/json'
}

response = requests.post(url, headers=headers, data=payload)
print(response.json())

const axios = require('axios');

const data = JSON.stringify({
  "source_image": "base64_or_url_of_live_selfie",
  "target_image": "base64_or_url_of_id_card",
  "threshold": 0.75
});

const config = {
  method: 'post',
  url: 'https://api.lumiid.com/v1/face-match/',
  headers: { 
    'Authorization': 'Bearer Your-Secret-Key', 
    'Content-Type': 'application/json'
  },
  data : data
};

axios.request(config)
.then((response) => console.log(response.data))
.catch((error) => console.log(error));

curl -X POST https://api.lumiid.com/v1/face-match/ \
-H "Authorization: Bearer Your-Secret-Key" \
-H "Content-Type: application/json" \
-d '{
  "source_image": "base64_encoded_string",
  "target_image": "base64_encoded_string",
  "threshold": 0.75
}'

Response Sample 200 OK

{
  "success": true,
  "code": "SUCCESS",
  "summary": {
    "verified": true,
    "verification_type": "FACE_MATCH"
  },
  "data": {
    "match_result": "CONFIRMED",
    "confidence": {
      "score": 0.9842,
      "threshold": 0.75,
      "status": "STRONG_MATCH"
    },
    "details": {
      "reason_code": "MATCH_SUCCESS",
      "remarks": "Identity verified successfully"
    }
  },
  "meta": {
    "request_id": "req_634490e898c1",
    "timestamp": "2026-03-10T17:45:12Z"
  }
}