Recognition Presets

Recognition presets

Aspose.BarCode for Java provides several recognition presets through QualitySettings.
These presets bundle multiple internal options (deconvolution, noise filters, search depth, etc.) to give you a convenient speed vs robustness trade-off:

  • QualitySettings.getHighPerformance() – favor speed on clean, high-quality images.
  • QualitySettings.getHighQuality() – enable additional recovery methods for degraded barcodes.
  • QualitySettings.getMaxQuality() – use the most exhaustive, slowest analysis for the toughest cases.

This article demonstrates how to apply these presets in practice based on the example class:

com.aspose.barcode.guide.recognition.performance.RecognitionPresets

You can find the full source code on GitHub:

RecognitionPresets.java

All snippets below assume that helper methods such as ExampleAssist.checkOrCreateImage(...) and ExampleAssist.assertRecognized(...) are available in your project.

1. Test data: clean vs degraded Code 128

The example class uses two types of barcode images:

  • Clean Code 128 – simple, high-contrast symbol generated at a comfortable size.
  • Blurred + noisy Code 128 – the same payload rendered larger and then degraded with blur and salt-and-pepper noise.

The clean image is generated as follows:

private void generateCode128Clean(String fullPath) throws IOException {
    BarcodeGenerator barcodeGenerator = new BarcodeGenerator(EncodeTypes.CODE_128, "SPEED-QUALITY-DEMO");
    barcodeGenerator.getParameters().getBarcode().getXDimension().setPixels(2);
    barcodeGenerator.getParameters().getBarcode().getBarHeight().setPixels(60);
    barcodeGenerator.save(fullPath, BarCodeImageFormat.PNG);
}

The degraded variant uses a custom blur + noise pipeline (simplified):

private void generateCode128BlurredNoisy(String fullPath) throws IOException {
    // 1) Render a larger, high-quality Code 128
    String hi = fullPath + ".hi.png";
    BarcodeGenerator barcodeGenerator = new BarcodeGenerator(EncodeTypes.CODE_128, "ROBUSTNESS-CHECK-123");
    barcodeGenerator.getParameters().getBarcode().getXDimension().setPixels(6);   // 3 * scale
    barcodeGenerator.getParameters().getBarcode().getBarHeight().setPixels(140);  // 70 * scale
    // ... configure generous quiet zones ...
    barcodeGenerator.save(hi, BarCodeImageFormat.PNG);

    // 2) Apply a light 3×3 box blur and salt & pepper noise
    BufferedImage src = ImageIO.read(Paths.get(hi).toFile());
    BufferedImage blurred = boxBlur(src);
    addSaltPepperNoise(blurred, 0.004);

    // 3) Downscale back to target size (bilinear interpolation)
    //    and save the final degraded image
    // ...
}

You do not need to replicate this degradation logic in your application; it is only used to produce deterministic test fixtures for comparing presets.

2. HighPerformance on clean barcodes

Use HighPerformance when:

  • you expect clean, high-quality barcodes (for example, generated labels),
  • you want to prioritize throughput and low CPU usage,
  • occasional difficult edge cases can be handled separately with more robust settings.

Example: fast recognition of a clean Code 128 symbol.

String fileName = "code128_clean.png";

ExampleAssist.checkOrCreateImage(IMAGES_FOLDER, fileName, this::generateCode128Clean);

QualitySettings qualitySettings = QualitySettings.getHighPerformance();
BarCodeReader barCodeReader = new BarCodeReader(
        Paths.get(IMAGES_FOLDER, fileName).toString(),
        DecodeType.CODE_128
);
barCodeReader.setQualitySettings(qualitySettings);

ExampleAssist.assertRecognized(barCodeReader, fileName, 1, DecodeType.CODE_128);

Key points:

  • Start from QualitySettings.getHighPerformance().
  • Pass this instance into barCodeReader.setQualitySettings(...) before calling readBarCodes() or helper methods.
  • On clean input, this preset should decode quickly while using fewer resources.

3. MaxQuality on clean images (thorough analysis)

MaxQuality enables the most exhaustive set of recognition procedures.

Example: using MaxQuality on a clean Code 128 image.

String fileName = "code128_max_quality.png";

ExampleAssist.checkOrCreateImage(IMAGES_FOLDER, fileName, this::generateCode128Clean);

QualitySettings qualitySettings = QualitySettings.getMaxQuality();
BarCodeReader barCodeReader = new BarCodeReader(
        Paths.get(IMAGES_FOLDER, fileName).toString(),
        DecodeType.CODE_128
);
barCodeReader.setQualitySettings(qualitySettings);

ExampleAssist.assertRecognized(barCodeReader, fileName, 1, DecodeType.CODE_128);

Note to example: even though MaxQuality is not required for clean images, running it on the same test input helps illustrate the trade-off: higher robustness potential vs longer processing time.

Recommendations:

  • Reserve MaxQuality for challenging inputs (poor lighting, severe distortions, difficult backgrounds).
  • For normal production flow, prefer NormalQuality or HighQuality and use MaxQuality in a fallback path or for re-processing.

4. HighQuality on blurred and noisy barcodes

HighQuality presets are targeted at degraded images: slight blur, noise, or poor contrast.
In the example, a Code 128 image is blurred, sprinkled with salt-and-pepper noise, and then downscaled. The HighQuality preset is used to recover it.

String fileName = "code128_blur_noise.png";

ExampleAssist.checkOrCreateImage(IMAGES_FOLDER, fileName, this::generateCode128BlurredNoisy);

QualitySettings qualitySettings = QualitySettings.getHighQuality();
BarCodeReader barCodeReader = new BarCodeReader(
        Paths.get(IMAGES_FOLDER, fileName).toString(),
        DecodeType.CODE_128
);
barCodeReader.setQualitySettings(qualitySettings);

ExampleAssist.assertRecognized(barCodeReader, fileName, 1, DecodeType.CODE_128);

Why HighQuality helps on damaged inputs:

  • it may enable more aggressive deconvolution and noise suppression,
  • it increases the search space for potential barcode candidates,
  • it can apply additional robustness filters that would be too expensive for realtime-only scenarios.

Use this preset when you cannot fully control input quality (for example, mobile cameras or scanned documents).

5. Measuring speed vs quality trade-off

The example class also contains a method that compares elapsed time for HighPerformance vs MaxQuality on the same image.
This test does not enforce any strict timing; it only prints measured values so you can estimate the relative cost.

String fileName = "compare_timing_high_quality.png";

ExampleAssist.checkOrCreateImage(IMAGES_FOLDER, fileName, this::generateCode128Clean);

// HighPerformance timing
BarCodeReader fastReader = new BarCodeReader(path(fileName), DecodeType.CODE_128);
fastReader.setQualitySettings(QualitySettings.getHighPerformance());
long t1 = System.nanoTime();
ExampleAssist.assertRecognized(fastReader, "HighPerformance timing", 1, DecodeType.CODE_128);
long fastMs = (System.nanoTime() - t1) / 1_000_000L;

// MaxQuality timing
BarCodeReader thoroughReader = new BarCodeReader(path(fileName), DecodeType.CODE_128);
thoroughReader.setQualitySettings(QualitySettings.getMaxQuality());
long t2 = System.nanoTime();
ExampleAssist.assertRecognized(thoroughReader, "MaxQuality timing", 1, DecodeType.CODE_128);
long thoroughMs = (System.nanoTime() - t2) / 1_000_000L;

System.out.println(
        "[Speed vs Quality] HighPerformance: " + fastMs + " ms; MaxQuality: " + thoroughMs + " ms"
);

How to use such measurements in your project:

  • Run similar tests on your own sample set (typical resolutions, camera devices, printers).
  • Log both recognition time and success rate (how many barcodes fail to decode).
  • Choose a preset (or combination of presets) that satisfies your latency budget while keeping failure rate acceptable.

6. Practical recommendations

When configuring recognition in a real application, a common strategy is:

  1. Start fast
    Use HighPerformance or NormalQuality for the first pass on incoming frames or images.

  2. Fallback on failure
    If no barcodes are recognized (or confidence is too low), re-run recognition on the same image with a more robust preset such as HighQuality or MaxQuality.

  3. Tune per scenario

    • For scanned documents or images captured in controlled conditions, NormalQuality or HighPerformance is often enough.
    • For mobile camera input (low light, perspective distortions, motion blur), consider HighQuality or a dedicated slow path for re-processing.

  4. Measure and iterate
    Use tests similar to compareTimingHighPerformanceVsMaxQuality() to collect timing statistics and make data-driven decisions about presets.

All examples in this article are based on:

RecognitionPresets.java

Use them as a template for integrating recognition presets into your own Java applications.

Quality Settings