Scan to Text
How to Batch Process Multilingual OCR with Aspose.OCR

How to Batch Process Multilingual OCR with Aspose.OCR

Digitizing global archives, business documents, or survey forms often means working with multiple languages. Manual extraction is slow and not scalable. Aspose.OCR for .NET lets you automate the extraction of text in various languages from large volumes of images or PDFs with just a few lines of code.

Real-World Problem

International companies, libraries, and data services often deal with mixed-language documents. Manual sorting and language-specific extraction are tedious and error-prone—especially when scaling up to thousands of documents.

Solution Overview

Aspose.OCR for .NET supports more than 30 languages. You can configure recognition settings per file or batch, then automate extraction and export to your preferred format for seamless integration into business or research workflows.

Prerequisites

  1. Visual Studio 2019 or later
  2. .NET 6.0 or later (or .NET Framework 4.6.2+)
  3. Aspose.OCR for .NET from NuGet
  4. Basic C# programming experience
PM> Install-Package Aspose.OCR

Step-by-Step Implementation

Step 1: Install and Configure Aspose.OCR 

using Aspose.OCR;

Step 2: Organize Input Files by Language

Organize your input images or PDFs by language in separate folders, or use a naming convention:

// Example folders: ./input/en, ./input/fr, ./input/zh

Step 3: Configure Recognition Settings Per Language 

Dictionary<string, Language> langFolders = new Dictionary<string, Language>
{
    { "en", Language.English },
    { "fr", Language.French },
    { "zh", Language.ChineseSimplified }
};

Step 4: Batch Process Input Files 

foreach (var pair in langFolders)
{
    string folder = "./input/" + pair.Key;
    RecognitionSettings settings = new RecognitionSettings();
    settings.Language = pair.Value;

    OcrInput input = new OcrInput(InputType.SingleImage);
    foreach (string file in Directory.GetFiles(folder, "*.png"))
    {
        input.Add(file);
    }

    AsposeOcr ocr = new AsposeOcr();
    List<RecognitionResult> results = ocr.Recognize(input, settings);

    foreach (RecognitionResult result in results)
    {
        string output = Path.Combine("./output/", pair.Key + "_" + Path.GetFileNameWithoutExtension(result.FileName) + ".txt");
        result.Save(output, SaveFormat.Text);
    }
}

Step 5: Add Error Handling and Automation 

try
{
    // batch processing code
}
catch (Exception ex)
{
    Console.WriteLine($"Error: {ex.Message}");
}

Step 6: Optimize for Speed and Accuracy

  • Run processing in parallel (with care for memory/CPU)
  • Use high-quality images for best results
  • Tune recognition settings for common layout features in each language
// Example: Parallel batch processing
Parallel.ForEach(langFolders, pair =>
{
    // per-language processing logic
});

Step 7: Complete Example 

using Aspose.OCR;
using System;
using System.Collections.Generic;
using System.IO;

class Program
{
    static void Main(string[] args)
    {
        try
        {
            Dictionary<string, Language> langFolders = new Dictionary<string, Language>
            {
                { "en", Language.English },
                { "fr", Language.French },
                { "zh", Language.ChineseSimplified }
            };

            foreach (var pair in langFolders)
            {
                string folder = "./input/" + pair.Key;
                RecognitionSettings settings = new RecognitionSettings();
                settings.Language = pair.Value;

                OcrInput input = new OcrInput(InputType.SingleImage);
                foreach (string file in Directory.GetFiles(folder, "*.png"))
                {
                    input.Add(file);
                }

                AsposeOcr ocr = new AsposeOcr();
                List<RecognitionResult> results = ocr.Recognize(input, settings);

                foreach (RecognitionResult result in results)
                {
                    string output = Path.Combine("./output/", pair.Key + "_" + Path.GetFileNameWithoutExtension(result.FileName) + ".txt");
                    result.Save(output, SaveFormat.Text);
                }
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine($"Error: {ex.Message}");
        }
    }
}

Use Cases and Applications

Global Archive Digitization

Automate extraction of text from multilingual archives, newspapers, or corporate records.

International Business Automation

Feed OCR results from mixed-language contracts, invoices, or HR documents into your global ERP or workflow.

Multilingual Compliance and Search

Enable full-text search and compliance checks across documents in many languages.

Common Challenges and Solutions

Challenge 1: Mixed-Language Documents

Solution: Run detection and processing per page, or use AUTO language mode if available.

Challenge 2: Varying Image Quality

Solution: Standardize scanning, and run pre-processing to normalize image quality.

Challenge 3: Performance Bottlenecks

Solution: Process in parallel where possible, and optimize resource usage.

Performance Considerations

  • Organize batch jobs by language for resource efficiency
  • Monitor memory/CPU with parallel jobs
  • Validate output on each batch

Best Practices

  1. Keep language folders organized for easy troubleshooting
  2. Validate a sample batch for each language
  3. Update Aspose.OCR for the latest language improvements
  4. Secure both input and output data

Advanced Scenarios

Scenario 1: Export Multilingual Results to JSON 

foreach (RecognitionResult result in results)
{
    result.Save(output.Replace(".txt", ".json"), SaveFormat.Json);
}

Scenario 2: Detect Language Automatically (if supported) 

settings.Language = Language.Auto;

Conclusion

Aspose.OCR for .NET lets you automate text extraction from diverse, multilingual image collections—speeding up global digitization and making your archives searchable, discoverable, and ready for workflow integration.

For a full list of supported languages and advanced tips, visit the Aspose.OCR for .NET API Reference .

 English