Dynamsoft

06/01/2026

Building an MRZ scanner for iOS? Here's the architecture decision most tutorials skip.

Real-time document scanning on mobile involves more than text recognition. It requires managing the camera session lifecycle, applying overlays, and determining when a frame is suitable for processing.

The stack we put together in SwiftUI:

→ AVFoundation for live camera feed
→ Document overlay to frame and detect the ID card boundary
→ Portrait overlay to confirm face presence before parsing
→ MRZ parsing only when alignment is confident
→ Structured output — name, DOB, document number, nationality

Omitting the face check can result in parsing blurry or incomplete frames. Without proper alignment, many scans may fail under real-world lighting conditions.

The tutorial walks through each layer with full SwiftUI code.

What's the trickiest part of your document capture flow on iOS? Let us know in the comments.

https://www.dynamsoft.com/codepool/ios-mrz-scanner-swiftui-face-detection.html?utm_medium=social&utm_campaign=Developer2026

05/29/2026

Blank separator pages in scanned document batches are easy to miss manually and time-consuming to remove at scale.

This tutorial uses Dynamic Web TWAIN’s IsBlankImageAsync() API to automatically detect blank pages, split multi-document batches at those points, and clean the output. Everything runs in the browser, with no server processing needed.

Full tutorial:
https://www.dynamsoft.com/codepool/blank-image-detection-web-twain.html?utm_medium=social&utm_campaign=Codepool2026

Learn how to use Dynamic Web TWAIN’s IsBlankImageAsync() to auto-detect and remove blank pages from scanned document batches in a browser-based JavaScript app.

05/29/2026

Pathology labs need more than fast scanning. They need traceability at every step.

Dynamsoft’s batch barcode scanning solution scans 150 cassettes in 30 seconds or less, handles curved and smudged labels, and supports LIMS integration with full audit documentation. Trusted by teams at Sakura Finetek and Takeda.

05/29/2026

Pathology labs need more than fast scanning. They need traceability at every step.

Dynamsoft’s batch barcode scanning solution scans 150 cassettes in 30 seconds or less, handles curved and smudged labels, and supports LIMS integration with full audit documentation. Trusted by teams at Sakura Finetek and Takeda.

Watch the video now!

05/28/2026

SDK upgrade notes describe improvements. Benchmark testing shows whether they’re real.

This tutorial builds a Python desktop tool using PySide6 and OpenCV that runs two versions of the Dynamsoft Capture Vision SDK in isolated subprocesses and renders barcode detection results side by side for direct visual comparison.

Full guide:
https://www.dynamsoft.com/codepool/python-package-version-comparison-tool.html?utm_medium=social&utm_campaign=Codepool2026

Learn how to build a Python script to compare pip package versions side by side using PySide6, OpenCV, and subprocess isolation — benchmark Dynamsoft Capture Vision SDK performance across versions with visual overlay results.

05/28/2026

Medication cabinets, contact lens drawers, and surgical supply trays are dense, high-SKU environments where scanning items one by one does not scale well.

Batch barcode scanning captures over 100 items in one pass, automatically counts SKUs, flags expired products, and creates a panoramic image for compliance documentation. This can reduce inventory time by up to 80%.

Read more:
https://www.dynamsoft.com/blog/insights/batch-barcode-scanning-medical-inventory/?utm_medium=social&utm_campaign=Batch2026

Streamline medical inventory management with batch barcode scanning—scan 100+ items instantly to save time, reduce errors, and boost clinic efficiency.

05/27/2026

When blur, glare, or physical damage causes barcode decoding to fail, OCR can serve as a practical fallback layer.

This tutorial pairs Dynamsoft Barcode Reader with Tesseract OCR in Python, using OCR to recover payloads from images that the barcode SDK cannot decode, improving resilience without replacing the primary scanning engine.

Implementation guide:
https://www.dynamsoft.com/codepool/tesseract-ocr-python-barcode.html?utm_medium=social&utm_campaign=Codepool2026

Learn how to read barcodes with Tesseract OCR in Python and improve barcode recognition accuracy for damaged images by combining Dynamsoft Barcode Reader with a Tesseract fallback — includes setup, sample code, validation strategy, and production troubleshooting tips.

05/27/2026

Manual barcode scanning slows down every stage of hospital operations, from receiving docks to pharmacy counters and pathology labs.

Batch scanning lets you capture over 100 barcodes in one pass. Processing time drops by up to 80%. Accuracy stays high across medication, sample intake, and supply audits.

Read more:

https://www.dynamsoft.com/blog/insights/hospital-inventory-automation-batch-barcode-scanning/?utm_medium=social&utm_campaign=Batch2026

05/26/2026

Dynamsoft Capture Vision 3.2.1000 introduces AI-powered models for 1D barcode decoding and MRZ recognition, including a deep learning model that delivers 42.7% faster MRZ processing.

This tutorial builds a Python benchmark tool that evaluates these models against public datasets with side-by-side performance comparisons.

Get started:
https://www.dynamsoft.com/codepool/ai-model-barcode-mrz-recognition.html?utm_medium=social&utm_campaign=Codepool2026

Learn how to build an AI-powered MRZ scanner and barcode reader using Dynamsoft Capture Vision 3.2.1000’s deep learning models — with benchmark results on real passport and 1D barcode datasets.

05/26/2026

A 99% lab accuracy rate can drop to 91% in production. At 1 million daily scans, that’s 90,000 failures.

Latency, device fragmentation, and backend bottlenecks each compound at scale in ways prototypes never reveal. This article breaks down where enterprise scanning systems fail and how to architect for production from the start.

Read more:
https://www.dynamsoft.com/blog/insights/enterprise-barcode-scanning-challenges/?utm_medium=social&utm_campaign=New2026