Released: Feb 5, 2026

11.4 での更新項目

機能

• AI-Powered Barcode Detection and Decoding
  • PDF417 Localization Model – Introduced the PDF417Localization neural network model for improved detection of PDF417 barcodes, especially under challenging conditions.
  • Code39/ITF Decoding Model – Added the Code39ITFDecoder model for enhanced decoding of Code 39 and ITF barcodes under blurred or low-resolution conditions.
  • Deblur Models for 2D Barcodes – Added the DataMatrixQRCodeDeblur and PDF417Deblur models to provide more effective recovery from motion and focus blur for DataMatrix, QR Code, and PDF417 barcodes.
• ECI (Extended Channel Interpretation) Support
  • ECI Information Return – Added support for retrieving Extended Channel Interpretation (ECI) data from barcodes. The new CECISegment class, along with the GetECISegmentsCount() and GetECISegment() methods in the CBarcodeResultItem and CDecodedBarcodeElement classes, enables access to character encoding information embedded in barcodes.
  • ECI-Based Text Interpretation – Added support for interpreting ECI segments during barcode decoding, improving compatibility with international character sets.
• Performance Improvements
  • On-Demand Model Loading – Implemented 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 – Enhanced confidence score calculation for results from neural network models, providing more accurate quality indicators.
  • DPM Barcode Optimization – Improved recognition rate for Direct Part Marking (DPM) barcodes commonly used in industrial and manufacturing environments.