dynamsoft_capture_vision_flutter 3.4.1300

The Dynamsoft Capture Vision Flutter SDK provides a wrapper for building barcode scanning, document scanning and MRZ scanning applications with Flutter SDK.

3.4.1300

Fixed

• Fixed crash and hang issues that could occur in certain scenarios.

3.4.1200

Highlights

AI-Powered Barcode Detection and Decoding

• PDF417 Localization Model – Introduces the PDF417Localization neural network model for improved detection of PDF417 barcodes, especially under challenging conditions.
• Code39/ITF Decoding Model – Adds the Code39ITFDecoder model for enhanced decoding of Code 39 and ITF barcodes under blurred or low-resolution conditions.
• Deblur Models for 2D Barcodes – Adds the DataMatrixQRCodeDeblur and PDF417Deblur models provide more effective recovery from motion and focus blur for DataMatrix, QR Code, and PDF417 barcodes.

ECI (Extended Channel Interpretation) Support

• ECI Information Return – Adds support for retrieving Extended Channel Interpretation (ECI) data from barcodes. The new [ECISegment]({{ site.dbr_flutter_api }}eci-segment.html) class, along with [getECISegments]({{ site.dbr_flutter_api }}barcode-result-item.html#getecisegments) method in [BarcodeResultItem]({{ site.dbr_flutter_api }}barcode-result-item.html) class, enables access to character encoding information embedded in barcodes.
• ECI-Based Text Interpretation – Adds support for interpreting ECI segments during barcode decoding, improving compatibility with international character sets.

Performance Improvements

• On-Demand Model Loading – Implements lazy loading for AI models, reducing initialization time by loading models only when first needed.
• Smart Model Selection – Models are now loaded based on configured barcode formats, minimizing memory usage by excluding unused models.
• Improved Confidence Scoring – Enhances confidence score calculation for results from neural network models, providing more accurate quality indicators.
• DPM Barcode Optimization – Improves recognition rate for Direct Part Marking (DPM) barcodes commonly used in industrial and manufacturing environments.

Identity Document Processing

• Enhanced Passport Processing – Improves document edge detection accuracy for passport documents through optimized processing workflows.
• Portrait Zone Detection – The MRZLocalization model now supports detecting portrait zone on identity documents, enabling automatic extraction of photo regions.

New

• Added BarcodeZoneWidthToHeightRatioRangeArray parameter for filtering barcodes based on aspect ratio constraints.
• Added setResultCrossVerificationCriteria and getResultCrossVerificationCriteria methods to MultiFrameResultCrossFilter for configurable multi-frame result verification.
• Added a new resolution max for capturing photos at maximum resolution (3024*4032).

Changed

• Barcode text encoding fallback changed from UTF-8 to ISO-8859-1 when no ECI information is present in the barcode.
• Updated default value of compensation parameter in ImageProcessor.convertToBinaryLocal from 0 to 10.
• convertToBinaryGlobal and convertToBinaryLocal of ImageProcessor class now support color and binary images as input in addition to grayscale images.

Removed

• Removed DataMatrixModuleIsotropic parameter – use BarcodeZoneWidthToHeightRatioRangeArray instead.
• Removed MinRatioOfBarcodeZoneWidthToHeight parameter – use BarcodeZoneWidthToHeightRatioRangeArray instead.

Improved

• Updated camera lifecycle management code to improve stability.

Fixed

• Fixed incorrect coordinate in barcode result when using neural network models with a specified region.
• Fixed crash and hang issues that could occur in certain scenarios.
• Fixed various minor bugs and improved overall stability.
• Fixed an issue where downloading deep learning models could fail.

3.2.5000

This release includes security maintenance updates to ensure continued protection of the product.

Security Updates

• Updated third-party libraries to incorporate the latest security fixes.

3.2.3000

🎉Milestone Release

Version 3.2.3000 introduces a series of AI-driven improvements designed to enhance barcode and MRZ detection accuracy, processing speed, and configuration flexibility.

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

AI-Powered MRZ Detection

• Neural MRZ Localization – The new MRZLocalization model improves region detection accuracy and delivers up to 42.7% faster processing for MRZ-based document workflows.
• Configurable Localization Control – The new LocalizationModes parameter allows configuration for text line detection.

Smart Document Capture

• Clarity-Based Frame Selection – Automatically selects the sharpest and highest-quality frame in live capture workflows.
• Cross-Frame Verification – Updated verification algorithms enhance result reliability.

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.

Document Workflows

• Improved performance in live video capture environments.
• Consistent document quality through clarity-based frame evaluation.
• Faster MRZ processing for high-throughput identity verification

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.

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 cameraToggleButton and cameraToggleButtonVisible, to the CameraView, allowing users to switch between the front and back cameras.
• Added AztecDetails, DataMatrixDetails, OneDCodeDetails, QRCodeDetails, allowing users to access detailed information for each barcode.
• Added ImageIO, ImageProcessor and ImageDrawer, allowing users to load, process, and draw images for easier image manipulation and visualization.
• Added the rawValue property to the ParsedField class, allowing users to access the original value of a parsed field.

Changes

• Refactored the getOriginalImage API by moving it from CaptureVisionRouter to IntermediateResultManager.
• ImageManager has been deprecated.

3.0.5200

• Improved barcode decoding performance.

  • Improved the reading rate of 1D barcode by introducing a new deblurring deep-learning model.
  • 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.
  • Added GS1 Application Identifiers (AI) support for improved code parsing capabilities.

• Added MRZ scanning support.

• Added document scanning support.

• Upgraded APIs to provide seamless integration with the new features.

• ⚠️ Breaking Changes:

• Removed all v1.4.0 apis and added new apis.