Image Text Finder
How to Detect and Report Sensitive Keywords or Watchlist Terms in Images

How to Detect and Report Sensitive Keywords or Watchlist Terms in Images

Businesses and organizations need to routinely scan digital image archives for the presence of blacklisted or sensitive terms to comply with security, HR, or regulatory mandates. Aspose.OCR Image Text Finder for .NET automates the detection and reporting of such keywords.

Real-World Problem

Manual inspection of image archives for banned or sensitive phrases is error-prone, time-consuming, and unscalable. Automated OCR-based search streamlines compliance and risk mitigation.

Solution Overview

With Aspose.OCR Image Text Finder, you can scan entire archives or folders of scanned images for terms on your organization’s watchlist, automatically flagging and logging any hits for review.

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. Sensitive keyword/watchlist in a text file (one term per line)
PM> Install-Package Aspose.OCR

Step-by-Step Implementation

Step 1: Prepare Your Sensitive Keyword/Watchlist File 

List<string> watchlist = new List<string>(File.ReadAllLines("watchlist.txt"));

Step 2: Configure Image Archive for Batch Scanning 

string[] imageFiles = Directory.GetFiles("./archive", "*.png", SearchOption.AllDirectories);
RecognitionSettings settings = new RecognitionSettings();
settings.Language = Language.English;
AsposeOcr ocr = new AsposeOcr();

Step 3: Scan Images for Watchlist Terms 

foreach (string image in imageFiles)
{
    foreach (string keyword in watchlist)
    {
        bool found = ocr.ImageHasText(image, keyword, settings);
        if (found)
        {
            File.AppendAllText("watchlist_hits.csv", $"{image},{keyword},found\n");
        }
    }
}

Step 4: Log, Report, or Alert on Keyword Hits

  • Append results to CSV, send automated emails, or flag in your system for human review.

Step 5: Review, Audit, and Optimize

  • Periodically review hit logs and tune your keyword/watchlist as policies change.
  • Test batch jobs for speed and accuracy on your archive.

Step 6: Complete Example 

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

class Program
{
    static void Main(string[] args)
    {
        try
        {
            List<string> watchlist = new List<string>(File.ReadAllLines("watchlist.txt"));
            string[] imageFiles = Directory.GetFiles("./archive", "*.png", SearchOption.AllDirectories);
            RecognitionSettings settings = new RecognitionSettings();
            settings.Language = Language.English;
            AsposeOcr ocr = new AsposeOcr();

            foreach (string image in imageFiles)
            {
                foreach (string keyword in watchlist)
                {
                    bool found = ocr.ImageHasText(image, keyword, settings);
                    if (found)
                        File.AppendAllText("watchlist_hits.csv", $"{image},{keyword},found\n");
                }
            }
        }
        catch (Exception ex)
        {
            File.AppendAllText("audit_errors.log", ex.Message + Environment.NewLine);
        }
    }
}

Use Cases and Applications

Security and Regulatory Compliance

Find banned phrases or confidential identifiers in business, legal, or government archives.

HR and Workplace Policy Enforcement

Spot inappropriate or policy-violating terms in digital documents or scanned records.

Digital Forensics and Investigations

Search for targeted names, accounts, or terms in evidence archives.

Common Challenges and Solutions

Challenge 1: Large Archives and Batch Jobs

Solution: Run overnight, split jobs, or parallelize as needed.

Challenge 2: Changing Policies or Watchlists

Solution: Keep watchlist.txt updated with current terms; review logs after each audit.

Challenge 3: Missed or False Positives

Solution: Tune OCR/image quality and watchlist; manually review flagged results.

Performance Considerations

  • Processing large archives can be resource-intensive—monitor disk and memory
  • Batch or schedule jobs off-hours to avoid business disruption
  • Secure log files for privacy and compliance

Best Practices

  1. Keep your watchlist current and reviewed by legal/compliance
  2. Log all hits and audit trails securely
  3. Automate regular scans and reviews
  4. Use high-quality input images for best accuracy

Advanced Scenarios

Scenario 1: Automated Alerting to Email or Slack

Trigger notifications to compliance officers on keyword hit.

Scenario 2: Integrate with DMS or Case Management

Auto-tag and flag files in your document management or investigation system.

Conclusion

Aspose.OCR Image Text Finder for .NET is a powerful tool for scanning image archives for sensitive, blacklisted, or policy keywords—enabling scalable, repeatable, and auditable compliance workflows.

Find more advanced scanning options in the Aspose.OCR for .NET API Reference .

 English