Table of contents
Swift
Objective-C

Release Notes for Java Edition - 11.x

11.2.1100 (10/28/2025)

Fixed

  • Resolved an initialization crash that occurred when running the SDK within the Spring Boot framework.

11.2.1000 (10/14/2025)

πŸŽ‰Milestone Release

Version 11.2.1000 introduces a series of AI-driven improvements designed to enhance barcode detection accuracy, processing speed, and configuration flexibility.

This release focuses on practical performance gains for production environments across retail, logistics, and manufacturing workflows.

✨ Key Highlights

AI-Powered Barcode Detection and Decoding

  • New Localization Models – Introduces OneDLocalization and DataMatrixQRCodeLocalization neural network models for improved detection of blurred / low-resolution 1D codes, or partially damaged DataMatrix/QR codes.
  • Specialized Decoders – Adds EAN13Decoder and Code128Decoder models optimized for long-distance and motion-blurred decoding scenarios.
  • Redesigned Deblur Model – The OneDDeblur model now provides more effective recovery from motion and focus blur.
  • Configurable Model Selection – The new ModelNameArray parameter supports flexible model loading and fine-grained control for specific barcode types.

Precision and Processing Control

  • Enhanced Deblur Methods – DM_DEEP_ANALYSIS now includes sub-level control with OneDGeneral, TwoDGeneral, and EAN13Enhanced options.
  • Barcode Count Expectation – The new ExpectedBarcodesCount parameter enables format-specific quantity control and early termination in fixed-count workflows.
  • Improved Region Detection – The new RPM_GRAY_CONSISTENCY mode provides more precise region extraction based on grayscale uniformity and local consistency for document and label processing.

Performance Highlights

Barcode Workflows

  • Up to 26.5% higher read rates under blur conditions with as much as 44% faster processing.
  • Reliable decoding of DataMatrix and QR codes with missing or damaged finder patterns.
  • Extended operational range beyond 75 cm for long-distance barcode scanning.

Developer Notes

  • Backward Compatibility – Fully compatible with existing integrations; no code-level changes required for upgrade.
  • Configuration Flexibility – Expanded parameter set allows comprehensive model configuration for scenario-specific tuning.
  • Production Stability – All new models validated in enterprise environments.

Changed

Parameter Defaults

  • MaxThreadsInOneTask: default changed from 4 β†’ 0 (auto-detection).
  • IncludeTrailingCheckDigit: default changed from 1 β†’ 0. Code128 results will no longer include the trailing check digit by default for improved compliance with standard decoding practices.

Deprecations

  • DeblurModelNameArray argument of DeblurModes β†’ use ModelNameArray.
  • AppendModelBuffer method of CaptureVisionRouter β†’ use AppendDLModelBuffer.

Fixed

  • Fixed a crash issue that occurred when calling initLicense.

11.0.6100 (08/19/2025)

Fixed

  • Fixed an issue where using a callback function could cause the program to crash.

11.0.6000 (08/06/2025)

Highlights

  • Workflow Improvements
    • Restructured the parameter control hierarchy at all levels for finer scope definition and more granular process management, with the stage level newly added.
    • Enabled custom combinations and sequences of sections, increasing flexibility and operational customization under specific conditions.
  • Deep Learning Integration
    • Improved the reading rate of 1D barcode by introducing a new deblurring deep-learning model.
  • Algorithm Enhancements
    • Enabled deduplication at the Region of Interest (ROI) level to consolidate results from multiple tasks.
    • Improved the CODE_128 and DataMatrix DeepAnalysis algorithms for better decoding accuracy and performance.
    • Added support for new barcode types: CODE_32, MATRIX_25, KIX, and TELEPEN.
  • Engineering Optimizations
    • Unified template-loading logic to reduce I/O overhead.
    • Added support for capturing data from multi-page files, including PDF and TIFF formats.
    • Implemented conversion functionality between ImageData and image files, including both on-disk and in-memory files.

This page is compatible for:

Is this page helpful?

YesYes NoNo

In this article: