Release Notes for iOS SDK - 11.x
11.2.3000 (11/05/2025)
Fixed
- Resolved an issue where
CaptureVisionRouter.startCapturingcould take longer than expected to complete. - Fixed a performance issue that caused slower continuous decoding when using an online license key.
Changed
- Updated the data types of the following properties in
DSPDF417Details:errorCorrectionLevel: fromNSDatatoNSArray<NSNumber>.hasLeftRowIndicator: fromNSIntegertoBOOL.hasRightRowIndicator: fromNSIntegertoBOOL.
11.2.1000 (10/16/2025)
πMilestone 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.
β¨ Key Highlights
AI-Powered Barcode Detection and Decoding
- New Localization Models β Introduces
OneDLocalizationandDataMatrixQRCodeLocalizationneural network models for improved detection of blurred / low-resolution 1D codes, or partially damaged DataMatrix/QR codes. - Specialized Decoders β Adds
EAN13DecoderandCode128Decodermodels optimized for long-distance and motion-blurred decoding scenarios. - Redesigned Deblur Model β The
OneDDeblurmodel now provides more effective recovery from motion and focus blur. - Configurable Model Selection β The new
ModelNameArrayparameter supports flexible model loading and fine-grained control for specific barcode types.
Precision and Processing Control
- Enhanced Deblur Methods β
DM_DEEP_ANALYSISnow includes sub-level control withOneDGeneral,TwoDGeneral, andEAN13Enhancedoptions. - Barcode Count Expectation β The new
ExpectedBarcodesCountparameter enables format-specific quantity control and early termination in fixed-count workflows. - Improved Region Detection β The new
RPM_GRAY_CONSISTENCYmode 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 β Fully compatible with existing integrations; no code-level changes required for upgrade.
- Configuration Flexibility β Expanded parameter set allows comprehensive model configuration for scenario-specific tuning.
- Production Stability β All new models validated in enterprise environments.
New
- Added a new method,
switchCapturingTemplate, which allows switching templates dynamically during the image processing workflow. - Added a new method,
clearDLModelBuffers, to release memory by clearing buffered deep learning models. - Added a new method,
setGlobalIntraOpNumThreads, to configure the global number of threads used for model execution. - Added a new button,
cameraToggleButton, to theCameraView, allowing users to switch between the front and back cameras. The following APIs are provided for configuring thecameraToggleButton:
11.0.5200 (08/18/2025)
Fixed
- Fixed an xcframework signature issue.
11.0.5100 (08/05/2025)
Fixed
- Small fixes and tweaks.
11.0.5000 (07/29/2025)
Changed
- License Validation Behavior: Instead of stopping execution immediately on an invalid license module, the library now continues processing and returns results from modules with valid licenses. An error is still reported to indicate the license issue.
- Default Camera Changed: To address short-distance focusing issues on Pro Max iPhones, the default camera has been switched to
BackDualWideAuto, enabling automatic switching between the wide and ultra-wide cameras.
Fixed
- Fixed various minor bugs and improved overall stability.
11.0.3000 (05/15/2025)
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.
- Implemented conversion functionality between
CImageDataand image files, including both on-disk and in-memory files.