Skip to content
  • Our Work
    • Fields
      • Cardiology
      • ENT
      • Gastro
      • Orthopedics
      • Ophthalmology
      • Pulmonology
      • Surgical Intelligence
      • Surgical Robotics
      • Urology
      • Other
    • Modalities
      • Endoscopy
      • Medical Segmentation
      • Microscopy
      • Ultrasound
  • Success Stories
  • Insights
    • Magazine
    • Upcoming Events
    • Webinars
    • Meetups
    • News
    • Blog
  • The company
    • About us
    • Careers
Menu
  • Our Work
    • Fields
      • Cardiology
      • ENT
      • Gastro
      • Orthopedics
      • Ophthalmology
      • Pulmonology
      • Surgical Intelligence
      • Surgical Robotics
      • Urology
      • Other
    • Modalities
      • Endoscopy
      • Medical Segmentation
      • Microscopy
      • Ultrasound
  • Success Stories
  • Insights
    • Magazine
    • Upcoming Events
    • Webinars
    • Meetups
    • News
    • Blog
  • The company
    • About us
    • Careers
Contact

Barcode Detection in complex environments

Automatically localizing and reading barcodes captured by a camera-based process have a great value for industrial and personal applications. A potential great benefit to the industry stems from relieving the constraint of human-guided scanning, which requires placing the scanner operator in close proximity to the barcode in order to obtain correct result. With camera-based scanning, product passing on a conveyor belt will not necessarily have to be aligned for the camera-based scanner to correctly detect the barcode.

Detect barcode or QR with camera-based scanners
Scan and detect QR-codes captured by a smartphone camera

With the availability of embedded cameras on smartphones, barcode scanning needs to operate in a less controlled environment. The challenges faced by barcode scanning in this case are thus far greater than in industrial settings. Main and crucial differences stem from: the quality of the image obtained, the motion blur involved in manually acquired images, unpredicted distance to barcode, non-uniform orientation and perspective, as well as unknown location of the barcode itself.
But whether for personal or industrial applications, barcode localization and scanning using camera-based system is a complex process. In complex scenes barcode localization is the crucial step towards a correct information retrieval. To reduce computation time, only candidate locations on an image are analyzed for being barcodes. For designated barcode readers, like bar or QR type codes, the system is acquired with a specific pattern to search for within the scene.
Candidate locations for barcode are searched using a designated template matching process, based either on the gradient map of the image or on feature matching. This stage is made as robust as possible to illumination changes, blur, orientation, perspective and distortion of the image. Complex pre-processing of the image is built to account expected complexities in the image, based on the designated operation of the scanner. In continuous acquisition of the scenes, the temporal relationship between subsequent frames can be exploited for stabilization and motion blur correction. However, it is probable that the system will reach its limits in case of sharp motion of the camera or object.
Upon localization of a candidate barcode position, the interpretation stage is initiated. With most barcode scanners the first step is binarization, although more complex color barcode has been recently proposed. When restricting the analysis to black and white, the greatest challenge in binarization of barcode in complex scenes is to compensate for motion blur.
Although barcode scanning is a common application in our daily life and most laser-based scanners offer nowadays outstanding performances, introducing camera-based scanners still requires much progress. Dealing with many of the mentioned complexities, localizing and interpreting a barcode in natural scenes require real expertise in image analysis and the construction of computer vision algorithms. At RSIP Vision we specialize in constructing computer vision and image processing algorithms for industrial and personal use. Visit our portfolio to see how RSIP Vision will take your application to the next level.

Share

Share on linkedin
Share on twitter
Share on facebook

Related Content

Percutaneous Nephrolithotomy

PCNL – Planning and real-time navigation

Prostate Tumor Segmentation

Implementing AI to Improve PI-RADS Scoring

RAS Navigation

Tissue Sparing in Robotic Assisted Orthopedic Surgeries

Procedural Planning in urology

Procedural Planning in Urology

C Arm X-Ray Machine Scanner

Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI

Visible spectrum color

Hyperspectral Imaging for Robotic Assisted Surgery

Percutaneous Nephrolithotomy

PCNL – Planning and real-time navigation

Prostate Tumor Segmentation

Implementing AI to Improve PI-RADS Scoring

RAS Navigation

Tissue Sparing in Robotic Assisted Orthopedic Surgeries

Procedural Planning in urology

Procedural Planning in Urology

C Arm X-Ray Machine Scanner

Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI

Visible spectrum color

Hyperspectral Imaging for Robotic Assisted Surgery

Show all

RSIP Vision

Field-tested software solutions and custom R&D, to power your next medical products with innovative AI and image analysis capabilities.

Read more about us

Get in touch

Please fill the following form and our experts will be happy to reply to you soon

Recent News

PR – Intra-op Virtual Measurements in Laparoscopic and Robotic-Assisted Surgeries

PR – Non-Invasive Planning of Coronary Intervention

PR – Bladder Panorama Generator and Sparse Reconstruction Tool

PR – Registration Module for Orthopedic Surgery

All news
Upcoming Events
Stay informed for our next events
Subscribe to Our Magazines

Subscribe now and receive the Computer Vision News Magazine every month to your mailbox

 
Subscribe for free
Follow us
Linkedin Twitter Facebook Youtube

contact@rsipvision.com

Terms of Use

Privacy Policy

© All rights reserved to RSIP Vision 2021

Created by Shmulik

  • Our Work
    • title-1
      • Ophthalmology
      • Uncategorized
      • Ophthalmology
      • Pulmonology
      • Cardiology
      • Orthopedics
    • Title-2
      • Orthopedics
  • Success Stories
  • Insights
  • The company