👥 Face Passive Liveness Detection (Face Spoofing Check)

👤 ระบบตรวจจับใบหน้าปลอม Face Anti-Spoofing Detection [iBeta Level 1 Certified]

Welcome to Face Passive Liveness Detection API, an AI product developed by iApp Technology Co., Ltd. Our API is designed to detect whether an input face image is genuine or fake, ensuring the authenticity of facial recognition processes. The API is certified by iBeta Level 1 and supports various techniques to identify face spoofing attempts.

Try Demo!

Example Images (Click to try)

API Key

Endpoint URL

cURL Command

Upload Image

Getting Started

Prerequisites
- An API key from iApp Technology
- Image files containing faces
- Supported formats: JPEG, JPG, PNG
- Maximum file size: 10MB
Quick Start
- Fast processing time
- High accuracy face spoofing detection
- Support for multiple file formats
- iBeta Level 1 certified accuracy
Key Features
- Face spoofing detection using various techniques
- Printed photos detection
- Realistic face mask for impersonation detection
- Detection of taken face photo from computer screen
- Video replays detection
- Detailed prediction scores and normalization
- Darkness level measurement
- Processing duration tracking
Security & Compliance
- GDPR and PDPA compliant
- No data retention after processing
- iBeta Level 1 certified security

How to get API Key?

Please visit API Key Management page to view your existing API key or request a new one.

Example

Face Passive Liveness Detection Request:

Image Preview

Face Detection Example

  curl --location 'https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness' \
      --header 'apikey: {YOUR API KEY}' \
      --form 'file=@"{YOUR UPLOADED FILE}"'

Face Passive Liveness Detection Response:

{
    "filename": "S__5333002.jpg",
    "predict": "SPOOF",
    "score": 0.9999989633974822,
    "darkness": 0.51,
    "data": {
        "SPOOF": 0.9999990463256836,
        "REAL": 9.35794162160164e-7
    },
    "normalized": {
        "SPOOF": 0.9999989633974822,
        "REAL": 1.0366025178232263e-6
    },
    "status_code": 200,
    "duration": 0.35393,
    "message": "SUCCESS"
}

Features & Capabilities

Core Features

Detects various face spoofing methods such as printed photos, realistic masks, computer screen images, and video replays.
Utilizes advanced deep learning techniques to ensure high accuracy and reliability.
Achieves over 99.43% accuracy across 7,680 tests.
Certified at iBeta Level 1 for secure and trusted face recognition systems.
Seamlessly integrates via RESTful API for easy deployment in applications.

Supported Fields

Detection of face spoofing attempts (printed photos, masks, screen images, video replays).
Detection confidence score for genuine vs. fake face.
Compatibility with popular image formats such as PNG, JPG, JPEG, HEIC, and HEIF.

API Endpoints

Endpoint	Method	Description	Cost
`POST /v3/store/ekyc/face-passive-liveness` Legacy: `/anti_face_spoofing`, `/api/v2/fas`, `/face-spoofing`, `/passive-face-liveness-detection`	POST	Face Liveness detection - detects spoofing attempts	0.3 IC per request
`POST /v3/store/ekyc/face-passive-liveness/v1p10` Legacy: `/v1p10/facial_anti_spoofing`	POST	Face Liveness detection (v1p10)	0.3 IC per request

API Reference

Face Passive Liveness Endpoints

1. Face Passive Liveness Detection (Base)

POST /v3/store/ekyc/face-passive-liveness

Detects whether a face image is genuine or a spoofing attempt. Supports detection of printed photos, realistic masks, screen captures, and video replays. iBeta Level 1 certified.

2. Face Passive Liveness Detection (v1p10)

POST /v3/store/ekyc/face-passive-liveness/v1p10

Alternative version of face passive liveness detection with enhanced algorithms for specific use cases.

Request & Response Format

Headers

Name	Type	Description
apikey	String	Your API Key to call this API

Request Body

Name	Type	Description
file	File	The binary data of the image

Response

{
    "filename": "Image.jpeg",
    "predict": "SPOOF",
    "score": 0.9999590674225165,
    "darkness": 0.29,
    "data": {
        "SPOOF": 0.9999197721481323,
        "REAL": 8.024471753742546e-5
    },
    "normalized": {
        "SPOOF": 0.9999590674225165,
        "REAL": 4.093257748349899e-5
    },
    "status_code": 200,
    "duration": 0.38198,
    "message": "SUCCESS"
}

Parameter in Response

Name	Type	Description
filename	String	File name
predict	String	Prediction result, either REAL or SPOOF, based on the normalized score
score	Float	Prediction score after normalization
darkness	Float	Darkness level as a percentage
data	Dictionary	Prediction scores for both REAL and SPOOF categories before normalization
normalized	Dictionary	Prediction scores for both REAL and SPOOF categories after normalization
status_code	Integer	Status code indicating success or error in processing
duration	Float	Processing time duration
message	String	Result or error message from processing

Code Examples

Curl

curl -X POST https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness \
    -H "apikey: YOUR_API_KEY" \
    -F "file=@/path/to/file.jpg"

Python

import requests

def detect_face_spoofing(image_path, api_key):
    url = "https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness"
    headers = {'apikey': {YOUR API KEY}}
    files = {'file': open(image_path, 'rb')}
    response = requests.post(url, headers=headers, files=files)
    return response.json()

JavaScript

const axios = require('axios');

async function detectFaceSpoofing(imagePath, apiKey) {
    const url = "https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness";
    const headers = { 'apikey': {YOUR API KEY} };
    const formData = new FormData();
    formData.append('file', fs.createReadStream(imagePath));

    try {
        const response = await axios.post(url, formData, { headers });
        return response.data;
    } catch (error) {
        console.error('Error:', error);
    }
}

PHP

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS => array('file'=> new CURLFILE('{YOUR UPLOADED FILE}')),
  CURLOPT_HTTPHEADER => array(
    'apikey: {YOUR API KEY}'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

Swift

let parameters = [
  [
    "key": "file",
    "src": "{YOUR UPLOADED FILE}",
    "type": "file"
  ]] as [[String: Any]]

let boundary = "Boundary-\(UUID().uuidString)"
var body = Data()
var error: Error? = nil
for param in parameters {
  if param["disabled"] != nil { continue }
  let paramName = param["key"]!
  body += Data("--\(boundary)\r\n".utf8)
  body += Data("Content-Disposition:form-data; name=\"\(paramName)\"".utf8)
  if param["contentType"] != nil {
    body += Data("\r\nContent-Type: \(param["contentType"] as! String)".utf8)
  }
  let paramType = param["type"] as! String
  if paramType == "text" {
    let paramValue = param["value"] as! String
    body += Data("\r\n\r\n\(paramValue)\r\n".utf8)
  } else {
    let paramSrc = param["src"] as! String
    let fileURL = URL(fileURLWithPath: paramSrc)
    if let fileContent = try? Data(contentsOf: fileURL) {
      body += Data("; filename=\"\(paramSrc)\"\r\n".utf8)
      body += Data("Content-Type: \"content-type header\"\r\n".utf8)
      body += Data("\r\n".utf8)
      body += fileContent
      body += Data("\r\n".utf8)
    }
  }
}
body += Data("--\(boundary)--\r\n".utf8);
let postData = body


var request = URLRequest(url: URL(string: "https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness")!,timeoutInterval: Double.infinity)
request.addValue("{YOUR API KEY}", forHTTPHeaderField: "apikey")
request.addValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")

request.httpMethod = "POST"
request.httpBody = postData

let task = URLSession.shared.dataTask(with: request) { data, response, error in
  guard let data = data else {
    print(String(describing: error))
    return
  }
  print(String(data: data, encoding: .utf8)!)
}

task.resume()

Kotlin

val client = OkHttpClient()
val mediaType = "text/plain".toMediaType()
val body = MultipartBody.Builder().setType(MultipartBody.FORM)
  .addFormDataPart("file","{YOUR UPLOADED FILE}",
    File("{YOUR UPLOADED FILE}").asRequestBody("application/octet-stream".toMediaType()))
  .build()
val request = Request.Builder()
  .url("https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness")
  .post(body)
  .addHeader("apikey", "{YOUR API KEY}")
  .build()
val response = client.newCall(request).execute()

Java

OkHttpClient client = new OkHttpClient().newBuilder().build();
MediaType mediaType = MediaType.parse("text/plain");
RequestBody body = new MultipartBody.Builder().setType(MultipartBody.FORM)
  .addFormDataPart("file","{YOUR UPLOADED FILE}",
    RequestBody.create(MediaType.parse("application/octet-stream"),
    new File("{YOUR UPLOADED FILE}")))
  .build();
Request request = new Request.Builder()
  .url("https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness")
  .method("POST", body)
  .addHeader("apikey", "{YOUR API KEY}")
  .build();
Response response = client.newCall(request).execute();

Dart

var headers = {
  'apikey': '{YOUR API KEY}'
};
var request = http.MultipartRequest('POST', Uri.parse('https://api.iapp.co.th/v3/store/ekyc/face-passive-liveness'));
request.files.add(await http.MultipartFile.fromPath('file', '{YOUR UPLOADED FILE}'));
request.headers.addAll(headers);

http.StreamedResponse response = await request.send();

if (response.statusCode == 200) {
  print(await response.stream.bytesToString());
}
else {
  print(response.reasonPhrase);
}

Accuracy and Performances

Achieves over 99.43% accuracy across 7,680 tests.
Certified at iBeta Level 1 for secure and trusted face recognition systems.

iBeta Certificate [iBeta Level 1]

This system is certified by iBeta Level 1 and is capable of detecting face spoofing attempts through various techniques, including printed photos, realistic face masks for impersonation, photos captured from computer screens, and video replays.

View iBeta Certificate Here

Pricing

Operation	Production Path	Legacy Path	IC Cost	Unit	On-Premise
Face Passive Liveness Detection	`/v3/store/ekyc/face-passive-liveness`	`/anti_face_spoofing`	0.3 IC	per 1 request	Contact us
Face Passive Liveness Detection (v1p10)	`/v3/store/ekyc/face-passive-liveness/v1p10`	`/v1p10/facial_anti_spoofing`	0.3 IC	per 1 request	Contact us

👥 Face Passive Liveness Detection (Face Spoofing Check)

Try Demo!

Example Images (Click to try)

Getting Started

Example

Face Passive Liveness Detection Request:

Face Passive Liveness Detection Response:

Features & Capabilities

Core Features

Supported Fields

API Endpoints

API Reference

Face Passive Liveness Endpoints

1. Face Passive Liveness Detection (Base)

2. Face Passive Liveness Detection (v1p10)

Request & Response Format

Headers

Request Body

Response

Parameter in Response

Code Examples

Curl

Python

JavaScript

PHP

Swift

Kotlin

Java

Dart

Accuracy and Performances

iBeta Certificate [iBeta Level 1]

Pricing

ChindaX

Speechflow

Try Demo!​

Example Images (Click to try)

Getting Started​

Example​

Face Passive Liveness Detection Request:​

Face Passive Liveness Detection Response:​

Features & Capabilities​

Core Features​

Supported Fields​

API Endpoints​

API Reference​

Face Passive Liveness Endpoints​

1. Face Passive Liveness Detection (Base)​

2. Face Passive Liveness Detection (v1p10)​

Request & Response Format​

Headers​

Request Body​

Response​

Parameter in Response​

Code Examples​

Curl​

Python​

JavaScript​

PHP​

Swift​

Kotlin​

Java​

Dart​

Accuracy and Performances​

iBeta Certificate [iBeta Level 1]​

Pricing​

Try Demo!

Getting Started

Example

Face Passive Liveness Detection Request:

Face Passive Liveness Detection Response:

Features & Capabilities

Core Features

Supported Fields

API Endpoints

API Reference

Face Passive Liveness Endpoints

1. Face Passive Liveness Detection (Base)

2. Face Passive Liveness Detection (v1p10)

Request & Response Format

Headers

Request Body

Response

Parameter in Response

Code Examples

Curl

Python

JavaScript

PHP

Swift

Kotlin

Java

Dart

Accuracy and Performances

iBeta Certificate [iBeta Level 1]

Pricing