Top ID Document OCR API alternatives in 2025

This response provides a comprehensive overview of the extracted data, including confidence levels and validity checks.

Pros and Cons:

• Pros: High accuracy in extracting MRZ data, easy integration, and support for multiple image formats.
• Cons: Limited to passport data extraction, which may not suit all use cases.

Ideal Use Cases: Identity verification, travel applications, and automated data entry for passport processing.

How It Differs from ID Document OCR API: While the ID Document OCR API supports a wide range of ID documents, the Passport OCR API specializes in extracting data specifically from passports, making it a more focused solution for passport-related applications.

2. Optical Character Recognition API

The Optical Character Recognition API is a versatile tool that allows users to extract any text from images. By simply passing the image URL, users can receive the text contained within it.

Key Features and Capabilities:

• Image Analysis: This feature enables users to extract text from images by providing the image URL. The API supports JPEG and PNG formats, with a maximum file size of 16 MB.

Example Response:

{
"results": [{
"status": {"code": "ok", "message": "Success"},
"name": "image_with_text.jpg",
"md5": "f556d7e2b92037ea8b6af4d731597f1d",
"width": 464,
"height": 479,
"entities": [{
"kind": "objects",
"name": "text",
"objects": [{
"box": [0.4547413793103448, 0.6868475991649269, 0.44396551724137934, 0.16075156576200417],
"entities": [{
"kind": "text",
"name": "text",
"text": "Sample text extracted from the image."
}]
}]
}]
}]
}

This response provides detailed information about the extracted text, including its position within the image.

Pros and Cons:

• Pros: Supports a wide range of image formats, flexible use cases, and high accuracy in text extraction.
• Cons: May require additional processing for complex layouts or handwritten text.

Ideal Use Cases: Digitizing printed documents, monitoring brand usage in images, and categorizing images based on text content.

How It Differs from ID Document OCR API: The Optical Character Recognition API is more general-purpose, allowing for text extraction from any image, while the ID Document OCR API focuses specifically on structured data extraction from various ID documents.

3. Japanese Driving License OCR API

The Japanese Driving License OCR API is designed to extract essential fields from Japanese driver's licenses, including name, residence, birthday, delivery date, expiration date, and personal number. This API supports various image formats, making it convenient for processing different types of driver's license images.

Key Features and Capabilities:

• Get Data: Users must provide the URL of an image, and the API will extract the relevant fields from the driver's license. It also allows users to specify whether they want to retrieve paragraphs of text.

Example Response:

{
"status": true,
"text": "氏名: 鈴木太郎\n生年月日: 1980年1月1日\n住所: 東京都新宿区\n有効期限: 2025年1月1日",
"boxCoordinates": [0.7516666666666667, 0.8366336633663366, 0.10666666666666667, 0.034653465346534656],
"paragraphs": [{
"text": "氏名: 鈴木太郎"
}]
}

This response provides a structured format for the extracted data, making it easy to access individual fields.

Pros and Cons:

• Pros: High accuracy for Japanese driver's licenses, supports multiple image formats, and automates data extraction.
• Cons: Limited to Japanese driver's licenses, which may not be applicable for international use cases.

Ideal Use Cases: Identity verification for onboarding processes, age verification for restricted products, and automating data entry for car rental services.

How It Differs from ID Document OCR API: The Japanese Driving License OCR API is specialized for Japanese licenses, while the ID Document OCR API supports a broader range of ID documents from various countries.

4. Handwriting to Text API

The Handwriting to Text API utilizes OCR technology to detect handwritten words in images and provides the extracted text in JSON format. This API is particularly useful for digitizing handwritten notes and documents.

Key Features and Capabilities:

• Text Extractor: Users can pass an image containing handwritten text, and the API will extract the text, returning it in a structured JSON format.

Example Response:

{
"results": [{
"status": {"code": "ok", "message": "Success"},
"name": "handwritten_note.jpg",
"md5": "ce00c14bb3398d44cc4757d11e6cf688",
"width": 800,
"height": 550,
"entities": [{
"kind": "objects",
"name": "text",
"objects": [{
"box": [0.095, 0.11818181818181818, 0.83625, 0.7872727272727272],
"entities": [{
"kind": "text",
"name": "text",
"text": "Last Wednesday we had a good team building."
}]
}]
}]
}]
}

This response provides a clear structure for the extracted handwritten text, including its position within the image.

Pros and Cons:

• Pros: Effective for digitizing handwritten content, flexible input options, and structured output.
• Cons: May struggle with illegible handwriting or complex layouts.

Ideal Use Cases: Digitizing handwritten notes, processing forms with handwritten entries, and analyzing handwritten content for data extraction.

How It Differs from ID Document OCR API: The Handwriting to Text API focuses specifically on handwritten text extraction, while the ID Document OCR API is designed for structured data extraction from various ID documents.

5. Text In Image Detection API

The Text In Image Detection API is a powerful tool for detecting and extracting text from images using OCR technology. It can be used for various purposes, including automated image captioning and indexing images.

Key Features and Capabilities:

• Text Detection: This feature detects text in the input image and converts it into machine-readable text. The response includes information about the recognized text, its location, and the accuracy of the detection.

Example Response:

{
"TextDetections": [{
"DetectedText": "Sample text detected in the image.",
"Type": "LINE",
"Id": 0,
"Confidence": 95.5,
"Geometry": {
"BoundingBox": {
"Width": 0.8666813373565674,
"Height": 0.03478481248021126,
"Left": 0.04065067321062088,
"Top": 0.01647869125008583
},
"Polygon": [{
"X": 0.04066945239901543,
"Y": 0.01647869125008583
}, {
"X": 0.9073320031166077,
"Y": 0.01696099154651165
}]
}
}]
}

This response provides detailed information about the detected text, including its confidence score and geometric data for visual representation.

Pros and Cons:

• Pros: Supports multiple languages, effective for low-resolution images, and provides structured output.
• Cons: May require additional processing for complex images or varying text orientations.

Ideal Use Cases: Automated image captioning, indexing images for search engines, and processing invoices.

How It Differs from ID Document OCR API: The Text In Image Detection API is designed for general text extraction from images, while the ID Document OCR API focuses on structured data extraction from specific ID documents.

6. PAN Card OCR API

The PAN Card OCR API extracts content from PAN cards, allowing users to store structured data efficiently. This API is particularly useful for organizations that need to process PAN card information.

Key Features and Capabilities:

• Create Job: This feature extracts data from PAN cards instantly and accurately. Users can create a job by passing the PAN card image URL and receive structured data in response.
• Get Request: Users can retrieve results from previously created jobs, allowing for efficient data management.

Example Response:

[{
"action": "extract",
"completed_at": "2022-12-26T23:51:58+05:30",
"created_at": "2022-12-26T23:51:57+05:30",
"group_id": "8e16424a-58fc-4ba4-ab20-5bc8e7c3c41e",
"request_id": "59875b82-889f-4872-ace6-203ad88ae26e",
"result": {
"extraction_output": {
"age": 40,
"date_of_birth": "1982-04-03",
"date_of_issue": "",
"fathers_name": "VASUDEV MAHTO",
"id_number": "ANRPM2537J",
"is_scanned": false,
"minor": false,
"name_on_card": "PRAMOD KUMAR MAHTO",
"pan_type": "Individual"
}
},
"status": "completed",
"task_id": "74f4c926-250c-43ca-9c53-453e87ceacd1",
"type": "ind_pan"
}]

This response provides a comprehensive overview of the extracted PAN card data, including personal details and status information.

Pros and Cons:

• Pros: Accurate extraction of PAN card data, structured output for easy integration, and efficient job management.
• Cons: Limited to PAN card data extraction, which may not be suitable for all applications.

Ideal Use Cases: Extracting information from PAN cards for compliance, identity verification, and data entry automation.

How It Differs from ID Document OCR API: The PAN Card OCR API is specialized for PAN card data extraction, while the ID Document OCR API supports a broader range of ID documents.

Conclusion

In conclusion, the choice of an OCR API depends on your specific needs and use cases. The ID Document OCR API is a versatile solution for extracting structured data from various ID documents, but the alternatives discussed here offer specialized capabilities that may better suit certain applications. For passport processing, the Passport OCR API is an excellent choice, while the Japanese Driving License OCR API is ideal for handling Japanese licenses. If you need general text extraction, the Optical Character Recognition API and the Text In Image Detection API provide robust solutions. For handwritten content, consider the Handwriting to Text API, and for PAN card processing, the PAN Card OCR API is your go-to option.

Evaluate your requirements carefully, and choose the API that aligns best with your project goals to enhance your document processing capabilities in 2025.