🛂 Passport OCR

🛂 พาสปอร์ต

Welcome to iApp Passport OCR API, an AI product developed by iApp Technology Co., Ltd. Our API is designed to automatically recognize and extract information from scanned passport images with high accuracy and speed. The system specifically focuses on reading the Machine Readable Zone (MRZ) at the bottom of passport pages, extracting crucial information like the holder's name, nationality, date of birth, and more.

Try Demo!

Example Images (Click to try)

API Key

Demo key is limited to 10 requests per day per IP
Click here to get your API key

Endpoint URL

cURL Command

Upload Passport

Getting Started

Prerequisites
- An API key from iApp Technology
- Scanned passport images (profile page)
- Supported file formats: JPEG, JPG, PNG, PDF
- Maximum file size: 10MB
Quick Start
- Fast processing (1-2 seconds per image)
- High accuracy text extraction (95.51%)
- Support for multiple file formats
Key Features
- Extracts information from TD3 type MRZ
- OCR accuracy scoring and validation
- Face image extraction in base64 format
- Support for multiple page PDF documents
- Handles rotated and skewed images
- Image segmentation pre-processing for skewed images
- Supports Thai and English language
Security & Compliance
- GDPR and PDPA compliant
- No data retention after processing

How to get API Key?

Please visit API Portal to view your existing API key or request a new one.

Example

Profile Page

Example Passport Profile Page

Request:

curl -X POST https://api.iapp.co.th/passport-ocr/v2/ocr \
-H "apikey: YOUR_API_KEY" \
-F "file=@/path/to/passport.jpg"

Response:

{
    "check_composite": "4",
    "check_date_of_birth": "4",
    "check_expiration_date": "4",
    "check_number": "6",
    "check_personal_number": "3",
    "country": "THA",
    "date_of_birth": "930710",
    "expiration_date": "250304",
    "method": "direct",
    "mrz_type": "TD3",
    "names": "MATHANIDA",
    "nationality": "THA",
    "number": "AC1062346",
    "personal_number": "0012345678913",
    "raw_text": "P<THAPOSHNASWADIWONG<<MATHANIDA<<<<<<<<<<<<<\nAC10623466THA9307104F25030440012345678913<34",
    "sex": "F",
    "surname": "POSHNASWADIWONG",
    "type": "P",
    "valid_composite": true,
    "valid_date_of_birth": true,
    "valid_expiration_date": true,
    "valid_number": true,
    "valid_personal_number": true,
    "valid_score": 100,
    "face": "/9j/4AAQSkZJRgABAQAAAQABAAD/..."
}

Response Fields Explanation

Field	Description	Format	Example
check_composite	Overall check digit for upper and middle machine readable lines	Single digit	"4"
check_date_of_birth	Check digit for date of birth field	Single digit	"4"
check_expiration_date	Check digit for expiration date field	Single digit	"4"
check_number	Check digit for document number	Single digit	"6"
check_personal_number	Check digit for personal number	Single digit	"3"
country	Country code of passport issuance	3 letters	"THA"
date_of_birth	Date of birth	YYMMDD	"930710"
expiration_date	Document expiry date	YYMMDD	"250304"
method	Reading method used	String	"direct"
mrz_type	Type of machine readable zone	String	"TD3"
names	First/given name(s)	String	"MATHANIDA"
nationality	Nationality of holder	3 letters	"THA"
number	Passport number	String	"AC1062346"
personal_number	National ID number	String	"0012345678913"
raw_text	Raw MRZ text from passport	String	"P<THAPOSHNASWADIWONG..."
sex	Gender	Single letter	"F"
surname	Last/family name	String	"POSHNASWADIWONG"
type	Document type	String	"P"
valid_composite	Overall MRZ validity check	Boolean	true
valid_date_of_birth	Date of birth check digit validity	Boolean	true
valid_expiration_date	Expiry date check digit validity	Boolean	true
valid_number	Document number check digit validity	Boolean	true
valid_personal_number	Personal number check digit validity	Boolean	true
valid_score	Overall validity score	Integer 0-100	100
face	Extracted face image	Base64 string	"/9j/4AAQSkZJRgABA..."

PDF File Processing

When processing PDF files, the response format differs slightly:

The response will be a JSON array containing results for each page
Each page result includes:
- page: Page number
- info: Contains all the standard fields as shown above
A process_time field shows total processing duration

Example PDF response structure:

[
    {
        "page": 1,
        "info": {
            "sex": "F",
            "number": "AC1062346",
            "expiration_date": "04/03/25",
            "raw_text": "P<THAPOSHNASWADIWONG<<MATHANIDA<<<<<<<<<<<<<\nAC10623466THA9307104F25030440012345678913<34",
            "personal_number": "0012345678913",
            "surname": "POSHNASWADIWONG",
            "nationality": "THA",
            "date_of_birth": "10/07/93",
            "names": "MATHANIDA",
            "country": "THA",
            "face": "iVBORw0...CYII=",
            "inference": "3.888",
            "file_name": "1676365480.3823211_thai_passport_page_1.png",
            "message": "Success",
            "status_code": 200
        }
    },
    {
        "process_time": "4.918s"
    }
]

Features & Capabilities

Core Features

MRZ (Machine Readable Zone) text extraction
Face image extraction
Multiple page PDF support
Automatic image orientation correction
Image segmentation for skewed images
High accuracy validation checks

Supported Fields

Document type
Issuing country
Document number
Holder's name
Nationality
Date of birth
Gender
Expiration date
Personal number
Face image (base64)
Raw MRZ text
Validation scores

API Reference

Recognizing Passport

POST https://api.iapp.co.th/passport-ocr/v2

Performs OCR on passport profile page and extracts MRZ data

Parameters:

file (required): Image file (JPG, PNG, PDF)
apikey (required): Your API key
options: Enable "segmentation" for skewed image processing

Code Examples

Python

import requests

url = "https://api.iapp.co.th/passport-ocr/v2/ocr"
headers = {
"apikey": "YOUR_API_KEY"
}
files = {
"file": open("passport.jpg", "rb")
}

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

JavaScript

const axios = require("axios")
const FormData = require("form-data")
const fs = require("fs")

let data = new FormData()
data.append("file", fs.createReadStream("passport.jpg"))

let config = {
    method: "post",
    url: "https://api.iapp.co.th/passport-ocr/v2/ocr",
    headers: {
        apikey: "YOUR_API_KEY",
        ...data.getHeaders(),
    },
    data: data,
}

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

PHP

<?php
$curl = curl_init();

curl_setopt_array($curl, array(
CURLOPT_URL => 'https://api.iapp.co.th/passport-ocr/v2/ocr',
CURLOPT_RETURNTRANSFER => true,
CURLOPT_POST => true,
CURLOPT_HTTPHEADER => array(
    'apikey: YOUR_API_KEY'
),
CURLOPT_POSTFIELDS => array(
    'file'=> new CURLFILE('passport.jpg')
)
));

$response = curl_exec($curl);
curl_close($curl);
echo $response;

Swift

import Foundation

let url = URL(string: "https://api.iapp.co.th/passport-ocr/v2/ocr")!
let boundary = "Boundary-\(UUID().uuidString)"

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "apikey")
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")

let imageData = try! Data(contentsOf: URL(fileURLWithPath: "passport.jpg"))

var body = Data()
body.append("--\(boundary)\r\n")
body.append("Content-Disposition: form-data; name=\"file\"; filename=\"passport.jpg\"\r\n")
body.append("Content-Type: image/jpeg\r\n\r\n")
body.append(imageData)
body.append("\r\n--\(boundary)--\r\n")

let task = URLSession.shared.uploadTask(with: request, from: body) { data, response, error in
    if let data = data {
        let json = try? JSONSerialization.jsonObject(with: data)
        print(json ?? "")
    }
}
task.resume()

Kotlin

import okhttp3.*
import java.io.File

val client = OkHttpClient()

val file = File("passport.jpg")
val requestBody = MultipartBody.Builder()
    .setType(MultipartBody.FORM)
    .addFormDataPart(
        "file",
        file.name,
        RequestBody.create(MediaType.parse("image/jpeg"), file)
    )
    .build()

val request = Request.Builder()
    .url("https://api.iapp.co.th/passport-ocr/v2/ocr")
    .addHeader("apikey", "YOUR_API_KEY")
    .post(requestBody)
    .build()

client.newCall(request).execute().use { response ->
    println(response.body()?.string())
}

Java

import java.io.*;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.file.*;

public class PassportOCR {
    public static void main(String[] args) throws IOException {
        String boundary = "Boundary-" + System.currentTimeMillis();
        URL url = new URL("https://api.iapp.co.th/passport-ocr/v2/ocr");
        HttpURLConnection conn = (HttpURLConnection) url.openConnection();

        conn.setRequestMethod("POST");
        conn.setDoOutput(true);
        conn.setRequestProperty("apikey", "YOUR_API_KEY");
        conn.setRequestProperty("Content-Type", "multipart/form-data; boundary=" + boundary);

        try (OutputStream os = conn.getOutputStream()) {
            byte[] fileBytes = Files.readAllBytes(Paths.get("passport.jpg"));

            os.write(("--" + boundary + "\r\n").getBytes());
            os.write(("Content-Disposition: form-data; name=\"file\"; filename=\"passport.jpg\"\r\n").getBytes());
            os.write(("Content-Type: image/jpeg\r\n\r\n").getBytes());
            os.write(fileBytes);
            os.write(("\r\n--" + boundary + "--\r\n").getBytes());
        }

        try (BufferedReader br = new BufferedReader(new InputStreamReader(conn.getInputStream()))) {
            String line;
            while ((line = br.readLine()) != null) {
                System.out.println(line);
            }
        }
    }
}

Dart

import 'package:http/http.dart' as http;
import 'dart:io';

Future<void> scanPassport() async {
    var url = Uri.parse('https://api.iapp.co.th/passport-ocr/v2/ocr');
    var request = http.MultipartRequest('POST', url);

    request.headers['apikey'] = 'YOUR_API_KEY';

    request.files.add(
    await http.MultipartFile.fromPath(
        'file',
        'passport.jpg',
    ),
    );

    var response = await request.send();
    var responseBody = await response.stream.bytesToString();
    print(responseBody);
}

Limitations and Best Practices

Limitations

Maximum file size: 10MB
Supported formats: JPG, PNG, PDF
One passport per image
Clear, focused images required

Best Practices

Ensure good lighting conditions
Avoid glare and reflections
Center the passport in frame
Keep the passport flat
Use high resolution images
Enable segmentation option for skewed images

Accuracy & Performance

Overall Accuracy

Current Version (2.0): 95.51%
Previous Version (1.1): 88.86%

Field-Level Accuracy (Version 1.1)

Name: 81.93%
Surname: 90.26%
Document Number: 84.03%
Nationality: 88.09%
Face Detection: 100%

Processing Speed

Single image: 1-2 seconds
PDF documents: 2-3 seconds per page
Additional time when using segmentation

Factors Affecting Accuracy

Image quality
Lighting conditions
Document positioning
Image resolution
Document condition
Image skew angle

History

Version 2.0 (February 2023)

Increased overall accuracy from 88.86% to 95.51%
Upgraded entire OCR engine
Added image segmentation pre-processing for skewed images

Version 1.1 (January 2023)

Added face extraction to base64
Added support for slightly tilted images
Added PDF file support
Added multiple page PDF support

Version 1.0 (February 2022)

Initial release
Support for all country passports using MRZ
Basic image format support (PNG, JPG, JPEG)

Pricing

AI API Service Name	Endpoint	IC Per Request	On-Premise
Passport OCR [v2.0]	passport_ocr_v1	0.75 IC/Request	Contact
Passport OCR [v2.0]	passport_ocr_v2	0.75 IC/Request	Contact

Try Demo!​

Example Images (Click to try)

Getting Started​

Example​

Profile Page​

Request:​

Response:​

Response Fields Explanation​

PDF File Processing​

Features & Capabilities​

Core Features​

Supported Fields​

API Reference​

Recognizing Passport​

Code Examples​

Python​

JavaScript​

PHP​

Swift​

Kotlin​

Java​

Dart​

Limitations and Best Practices​

Limitations​

Best Practices​

Accuracy & Performance​

Overall Accuracy​

Field-Level Accuracy (Version 1.1)​

Processing Speed​

Factors Affecting Accuracy​

History​

Version 2.0 (February 2023)​

Version 1.1 (January 2023)​

Version 1.0 (February 2022)​

Pricing​