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Endpoint

POST /api/auth/image-login

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Overview

This endpoint uses Optical Character Recognition (OCR) to extract student information from a college ID card photo. It processes the image to extract the enrollment number and name, then generates a user ID in the college email format.
This is an alternative authentication method that doesn’t require a pre-existing account. The system extracts credentials directly from the ID card.

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Request

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Content Type

multipart/form-data

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Request Body

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image
file
required
College ID card image fileSupported formats: JPG, PNG, JPEGRequirements:
  • Clear, well-lit photo of the ID card
  • Enrollment number must be visible (11-digit number)
  • Name field must be readable
  • Text should not be blurred or obscured

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Response

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status
string
Either "success" or "error"
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message
string
Description of the operation result
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user_id
string
Generated user ID in college email formatFormat: <firstname>.<lastname><first3digits>@adgitmdelhi.ac.inExample: [email protected]
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enrollment_no
string
Extracted 11-digit enrollment number from the ID card

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Example Request

cURL
curl -X POST http://localhost:3001/api/auth/image-login \
  -F "image=@/path/to/id-card.jpg"
JavaScript with FormData
const formData = new FormData();
formData.append('image', idCardFile); // File object from input

const response = await fetch('http://localhost:3001/api/auth/image-login', {
  method: 'POST',
  body: formData
});

const data = await response.json();
console.log('Generated User ID:', data.user_id);
React Example
function IdCardUpload() {
  const handleUpload = async (e) => {
    const file = e.target.files[0];
    const formData = new FormData();
    formData.append('image', file);

    try {
      const response = await fetch('/api/auth/image-login', {
        method: 'POST',
        body: formData
      });
      
      const data = await response.json();
      
      if (data.status === 'success') {
        console.log('User ID:', data.user_id);
        console.log('Enrollment:', data.enrollment_no);
        // Use the generated user_id for subsequent signup/login
      }
    } catch (error) {
      console.error('OCR failed:', error);
    }
  };

  return (
    <input 
      type="file" 
      accept="image/*" 
      onChange={handleUpload} 
    />
  );
}

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Example Responses

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Success Response

200 OK
{
  "status": "success",
  "message": "OCR verification successful",
  "user_id": "[email protected]",
  "enrollment_no": "12345678901"
}

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Error Responses

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No Image Uploaded

400 Bad Request
{
  "status": "error",
  "message": "No image uploaded."
}

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Enrollment Number Not Found

400 Bad Request
{
  "status": "error",
  "message": "Enrollment number not found in the ID card."
}

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Name Not Readable

400 Bad Request
{
  "status": "error",
  "message": "Name not found or unreadable on the ID card."
}

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OCR Processing Failed

500 Internal Server Error
{
  "status": "error",
  "message": "OCR failed to process image."
}

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How It Works

1

Image Upload

Client uploads ID card image via multipart/form-data
2

OCR Processing

Server uses Tesseract.js to extract text from the image
server.js
const result = await Tesseract.recognize(imagePath, 'eng');
const extractedText = result.data.text;
3

Enrollment Number Extraction

System searches for an 11-digit number in the extracted text
const enrollmentMatch = extractedText.match(/\b\d{11}\b/);
const enrollmentNo = enrollmentMatch?.[0];
4

Name Extraction

System extracts the name from the “Name:” field
const nameMatch = extractedText.match(/Name\s*:\s*(.*)/i);
let name = nameMatch?.[1]?.trim()
  .split(' ')
  .slice(0, 2)  // Take first two words
  .join('.')
  .toLowerCase();
5

User ID Generation

Combines name and first 3 digits of enrollment numberFormat: <firstname>.<lastname><digits>@adgitmdelhi.ac.inExample: [email protected]

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Best Practices

This endpoint returns a user ID but does NOT create an account or return a JWT token. You must use the generated user_id with the Signup endpoint to create an account.

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Image Quality Tips

  • Lighting: Ensure good lighting without glare or shadows
  • Focus: Image should be clear and in focus
  • Orientation: ID card should be right-side up
  • Background: Plain background improves OCR accuracy
  • Resolution: Higher resolution improves text recognition

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Integration Flow

Complete Authentication Flow
// 1. Upload ID card for OCR
const ocrResponse = await fetch('/api/auth/image-login', {
  method: 'POST',
  body: formData
});
const { user_id, enrollment_no } = await ocrResponse.json();

// 2. Use extracted user_id to create account
const signupResponse = await fetch('/api/auth/signup', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    email: user_id,
    password: userPassword
  })
});

// 3. Login with the new account
const loginResponse = await fetch('/api/auth/login', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    email: user_id,
    password: userPassword
  })
});

const { token } = await loginResponse.json();
// Now you have a JWT token for authenticated requests

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Technical Details

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OCR Engine

  • Library: Tesseract.js v6.0.1
  • Language: English (eng)
  • Training Data: Located at backend/eng.traineddata

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File Handling

  • Uploaded images are temporarily stored in backend/uploads/
  • Files are deleted after processing (success or failure)
  • Uses multer middleware for multipart form handling

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Security Considerations

Uploaded images are immediately deleted after OCR processing to prevent storage of sensitive ID card information.
  • Images are not permanently stored
  • No authentication token is generated by this endpoint
  • Rate limiting recommended to prevent abuse
  • Validate file types on client side before upload
  • Signup - Create account using extracted user ID
  • Login - Login with created credentials
  • Google Login - Alternative OAuth authentication

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