• container code recognition, serial shipping container code
  • SSCC, ISO 6346, intermodal container code, container number
OCR SOFTWARE FOR CONTAINER CODE RECOGNITION

OCR SOFTWARE FOR CONTAINER CODE RECOGNITION

CARMEN® AUTOMATIC CONTAINER CODE RECOGNITION (ACCR)

is created to extract and read the identification codes of ISO 6346 intermodal containers. This ISO code reading capability of shipping containers makes logistics environments more intelligent by building comprehensive databases tracking container movement, automating and simplifying railway or harbor logistics, assisting border control and container surveillance systems. CARMEN® ACCR reads the container codes from digital still images, digital image flow or live video signal. The unique serial number with check digit, owner, country code, size, type and equipment category as well as operational marks (if any) of every cargo container are returned with the highest accuracy available on the market.

Additional Info

  • BENEFITS: BENEFITS CARMEN® ACCR offers:
    • High accuracy and industry leading high recognition rates
    • Increased accuracy and security for logistic supply chains
    • Smooth and problem-free 24/7 operation
    • Easy integration through SDK and user-friendly API

      • CARMEN® ACCR provides solution for common problems by:
        • Automating ISO 6346/MOCO code reading that saves time and resources
        • Allowing faster, more accurate inventory tracking and surveillance
        • Enabling and maintaining real-time container location tracking

          • CARMEN® ACCR is ideal for:
            • Maritime, harbour and landside logistics and inventory management
            • Terminal, port traffic and security system support
            • Business intelligence and real-time inventory analytics
            • SPECS: SPECIFICATIONS

              CARMEN® ACCR offers the advantage with its ability to automatically recognize any vertically and horizontally aligned ISO 6346 (BIC), MOCO (Montan Container), and dimension codes from an image source (e.g. analog or digital cameras; line scanners), and by adapting to environmental changes for 24/7 operation. It is fast, easy and straightforward to use, and multiple image and image sources process the same container code to ensure high recognition accuracy. Its development libraries (DLL, SO) allow flexible integration through their SDK on both Windows and Linux platforms; 32&64 bit; x86, ARM, power PC, and in server mode CARMEN® ACCR is able to perform parallel processing and handling of unlimited camera inputs.

               

              GENERAL INFORMATION
              Purpose Automatic recognition of the container codes – a ISO container code recognition software for logistic systems (railway, marine, harbours and airports), supporting ISO 6346 (BIC code) and MOCO code
              Supported operating systems Windows (32/64 bit)
              Linux (32/64 bit)
              Supported platforms x86_32 | x86_64 |
              Minimum system requirements 1 GHz CPU | 512 MB RAM | 1 GB HDD | free port/slot for NNC
              Licensing One licence per application thread, multiple license/controller is available
              Available neural network controllers USB 2.0 – type A
              USB – internal, 4 pin
              PCIe card (x1)
              mini-PCIe card (x1) (new!)
              INTERFACE
              Input Still image from file or memory in any image format
              (BMP | PNG | JPEG | JPEG2K | RAW)
              Live analog video input (PAL or NTSC)
              Live digital camera input
              Output OCR data
              ISO Container code in ASCII text
              Position of the code
              Confidence level in percentage
              Confidence levels for each characters
              ID of the best image
              Trigger Can be integrated with any trigger device (recommended when recognizing from live image stream)
              Software motion detection module is included
              DEVELOPMENT TOOLS
              Supported programming languages under Windows C/C++, C#
              Visual Basic .NET
              Java
              Supported programming languages under Linux C/C++, Java
              In the box Development libraries: .dll, .so files
              Demo application, sample codes for each progamming language
              Neural network controller
              Comprehensive digital documentation available online

               

              Technical specifications are subject to change without prior notice. This document does not constitute an offer.

            • DESCRIPTION: DESCRIPTION

              CARMEN® ACCR offers the advantage to automatically recognize any vertically and horizontally aligned international standard container codes:

              • ISO 6346 (BIC)
              • MOCO (Montan Container)
              • ILU (European Intermodal Loading Units)
              • and dimension codes

              The image source can either be analog or digital IP cameras. By adding illumination to the cameras, the software is able to adapt to the environmental changes for a smooth 24/7 operation. It is fast, easy and straightforward to use.

              CARMEN® ACCR has the capability to receive multiple images from multiple image sources to process the same container code and ensure high recognition accuracy.

              Its development libraries (DLL, SO) allow flexible integration on both Windows and Linux platforms. In server mode CARMEN® ACCR is able to perform parallel processing and handling of unlimited camera inputs.

            • MEDIA: MEDIA carmen

              LINKS & DOWNLOADS
               
              CARMEN® ACCR SOFTWARE BROCHURE pdf   Product description in PDF
               
              CARMEN® SOFTWARE VERSIONS pdf   A comprehensive review of all CARMEN® software versions
               
              ARH PRODUCT CATALOG pdf   Comprehensive brochure showcasing all of our traffic, license plate recognition, passport, travel document, ID reader and biometric (AFS/AFIS) products
               
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