Read text from shipping labels, licenses, component markings, and damaged barcodes with integrated OCR capabilities on Datalogic scanners.

In enterprise environments, damaged or poorly printed barcodes can significantly impact productivity. Traditional scanning solutions either fail completely or require operators to manually transcribe the human-readable text beneath barcodes - a time-consuming and error-prone process. SnapOCR bridges this gap by combining barcode scanning with intelligent OCR technology in a single, unified workflow.

Overview

Datalogic introduces SnapOCR, an innovative feature that combines traditional barcode scanning with optical character recognition (OCR) capabilities, enabling devices to capture and process human-readable text when barcodes are damaged, poorly printed, or need supplementary data extraction. This feature addresses critical operational challenges in warehousing, logistics, and retail environments where label quality varies or where capturing additional text information alongside barcodes adds value to workflows.

SnapOCR operates as an intelligent fallback system—when standard barcode decoding encounters difficulties, the feature automatically engages OCR technology to read the human-readable text typically printed above or below barcodes, ensuring data capture success even in challenging conditions. Beyond recovery scenarios, SnapOCR enables sophisticated multi-data capture workflows, such as simultaneously reading license plates, shipping labels with multiple text fields, or documents requiring structured data extraction.

How SnapOCR Works

The feature offers three distinct operational modes to match different use cases:

Selection Modes

Always Propose/Send: Searches the entire camera frame for text, ignoring any ROI definitions. The system either proposes found text for user selection (Propose) or sends it directly (Send). This mode excels when dealing with damaged barcodes where the exact text location is unpredictable.

ROI (Region of Interest): Defines specific areas within the frame where text should be captured. Users can configure a Reference ROI matching the label form factor, then define multiple Internal ROIs for specific data fields. Each ROI can have its own regex filter for validation and a prefix for identification in the output stream.

PickList: Focuses OCR processing near the center pointer, similar to picklist barcode scanning. This mode optimizes performance when operators can aim at specific text areas, reducing processing overhead and improving response times.

Scanning Policies

SnapOCR integrates with standard scanning workflows through three policies:

  • OCR and Barcode: Attempts barcode decoding first, falling back to OCR if unsuccessful
  • OCR Only: Bypasses barcode decoding entirely
  • Trigger Based: Assigns OCR to specific triggers, allowing operators to choose between standard scanning and OCR capture

Advanced ROI Configuration

For structured documents like shipping labels or forms, SnapOCR supports sophisticated ROI (Region of Interest) configuration:

  • Define a Reference ROI matching your label form factor
  • Create multiple Internal ROIs for specific data fields
  • Apply RegEx filters to validate text structure
  • Add prefixes to identify data sources for post-processing

Practical Implementation

Use Case 1: Fallback for Damaged Barcodes

Configure SnapOCR with Scanning Policy set to "OCR and Barcode". When the scanner cannot decode a barcode, it automatically activates SnapOCR to capture the human-readable text, ensuring no disruption to workflow.

Use Case 2: Dedicated OCR Trigger

Using Datalogic's Advanced Keyboard Remapper, assign the right trigger to "OCR DECODE" while keeping the left trigger for standard barcode scanning. This gives operators instant access to both capabilities.

Use Case 3: Structured Data Capture

For applications like license plate reading or form processing, configure specific ROIs to capture only relevant text fields, with automatic validation through RegEx patterns.

Use Cases

SnapOCR is particularly valuable for:

  • Degraded barcode recovery: Automatic fallback when barcodes are damaged, faded, or poorly printed
  • License plate recognition: Capture vehicle registration information with ROI-based targeting for parking management and traffic applications
  • Document data extraction: Extract text from invoices, serial numbers, batch identifiers, or human-readable labels without requiring separate scanning applications
  • Quality assurance: Combine barcode data with OCR verification to validate product information, expiration dates, or batch traceability

Configuration and Deployment

SnapOCR integrates with Datalogic's deployment ecosystem:

  • Scan2Deploy Studio: Visual configuration interface with profile export and QR code generation for seamless device deployment
  • OEMConfig: Native Android Enterprise integration for fleet-wide management via EMM platforms
  • Datalogic SDK (for advanced applications): Programmatic control via SnapOcr, SnapOcrRoiSettings, and related classes for custom implementations

Device and Firmware Support

SnapOCR is available on the following Datalogic devices:

DeviceOSFirmware Version
Memor 30/35 Android 13 v1.07.003 or later
Memor 12/17 Android 13 Latest available
Skorpio X5 Android 11/13 v4.05 or later
Joya Touch 22 Android 11/13 Latest available

SDK Support: Core SnapOCR functionality is available in Datalogic SDK 1.38 and later. Advanced features—including automatic image cropping and frame capture for both barcode and OCR results—are available in SDK 1.45 (released July 1, 2025) and are being rolled out across supported devices.

Important Considerations

  • Send vs Propose modes: Use "Send" when data goes directly to text fields; use "Propose" when applications consume data programmatically
  • Performance: SnapOCR requires adequate lighting for optimal text recognition
  • Languages: Multiple language support available - check device documentation for specifics

Useful Links

Datalogic Resources

Related Documentation

Community Support

For deployment assistance or specific use case consultation, visit the Datalogic Discussion Forum