Algorithm Overview
This page provides a high-level overview of how Quagga2 processes images to detect and decode barcodes.
Processing Pipeline
Quagga2 processes each frame through a multi-stage pipeline:
Input Image → Preprocessing → Localization → Decoding → Result
1. Preprocessing
- Scaling: Image is resized based on
inputStream.size - Grayscale conversion: Color image converted to grayscale
- Area cropping: If
inputStream.areais set, crop to that region
2. Localization
When locate: true (default):
- Binarization: Convert to black/white using Otsu’s method
- Grid division: Split image into patches
- Skeletonization: Extract line structures
- Pattern analysis: Find barcode-like patterns
- Bounding box: Calculate barcode region
See How Barcode Localization Works for detailed explanation.
3. Decoding
- Scanline extraction: Sample pixels along detected barcode
- Pattern matching: Match bar/space patterns to barcode format
- Character decoding: Convert patterns to characters
- Checksum validation: Verify barcode integrity
Key Algorithms
Otsu’s Method
Automatic threshold selection for binarization. Adapts to varying lighting conditions by analyzing the image histogram.
Connected Component Labeling
Groups adjacent pixels into distinct regions. Used during localization to identify potential barcode patterns.
Image Moments
Mathematical technique to calculate orientation and position of detected patterns.
Performance Characteristics
| Factor | Impact | Mitigation |
|---|---|---|
| Image size | Linear increase | Use inputStream.size |
| Number of readers | Linear increase | Only enable needed readers |
| Localization | ~60% of processing time | Use locate: false if position known |
| Half sampling | 4x faster | Keep halfSample: true |
Related
- How Barcode Localization Works - Detailed localization explanation
- Architecture - Code structure overview
- Optimize Performance - Performance tuning