Move Over Laser Barcode Scanner

But what if you want to encode text descriptions along with tracking numbers, such manufacturing location, or an airline passenger’s physical characteristics and frequent flyer status along with their seat number? You can’t pack all that information into one row of lines, but you can in 2D data matrix code.

Unfortunately for most laser scanners, reading 2D codes isn’t possible. The growth in the use and amount of machine-readable data has led to growing interest in image-based readers that use machine vision technologies to process more complex codes, but these systems have traditionally lagged laser scanner technology on price and speed, despite offering several other advantages, such as the ability to read partially obscured or damaged codes and combine barcode reading with optical character recognition (OCR) – even handwritten addresses and notes.

Today, advances in semiconductor design and manufacturing that boost performance while cutting the cost of each microprocessors are helping image based scanners to achieve cost parity with laser scanners for many applications, while still adding several important advantages.

High-Speed Reads
“With the camera technology today, VITRONIC has been able to make the camera-based 2D data matrix code reader as fast as a 1D laser-based barcode scanner,” says Jay Stone, Vice President of Sales and Marketing at VITRONIC Machine Vision Ltd. (Louisville, Kentucky). “How fast? We’ve been able to read objects that we throw through the cameras’ field of view.”

Using a new, high performance, multi-core microprocessor architecture, VITRONIC’s VICAM^snap! auto-ID system for processing 1D and 2D barcodes can run in constant acquisition mode, at 200 dpi, eliminating the need for external triggering.

“By using the multi-core architecture on a single board computer inside the VICAM^snap!, we can be as fast as a laser scanner without needing to use active cooling,” adds Stone. “No fan or other moving parts means we’re more rugged than barcode scanners, which depend on moving mirrors to scan the laser across the barcode. We can also process images at 200 dpi, while most other image-based auto-ID readers work at 150 dpi. You need better than 150 dpi to effectively process the images for OCR in addition to code reading.

Market Intelligence News & Insights: 

How Will Apple’s $500 Billion Investment for US Manufacturing, Education, and AI Play Out?

On February 24^th, Apple announced a “commitment… to spend and invest more than $500 billion in the U.S. over the next four years”, with plans for new manufacturing plants, enhanced support for manufacturing partners via their Advanced Manufacturing Fund, and a myriad of other initiatives. As part of this plan, Apple projects 20,000 new hires, with roles focused on R&D, silicon engineering, software development, and AI/ML engineering.

Read More

When 1% Means $100,000s
One of the most important considerations for an auto ID system is read rate, both in terms of throughput and the percentage of real world codes that the system can read. When it comes to 1D and 2D codes, image based auto ID readers look at the entire code, not simply cross sections of the code like a laser scanner. That means as long as some part of the each line of code is present – in other words not completely missing – an image-based auto ID system can read it. Image based auto ID systems can also read codes with quite zone violations, poor contrast, distorted codes caused by perspective changes, unevenly printed or illuminated codes, and codes in noisy backgrounds.

Based one manufacturer’s research on image based auto ID readers, a high volume shipper that processes millions of packages per year can save more than $100,000 per year  by adopting an image-based auto ID system that delivers a 0.9% improvement in read rates compared to laser scanners.

Image based readers can also read codes marked in different colored inks because they use white LED illumination. Most laser based readers, for example, use a red laser, which can be ineffective when reading red ink used by many postal agencies, according to VITRONIC’s Stone. Image based readers can also read 1D and 2D bar codes in any direction. Most automated laser-based 1D barcode readers require label to be in a specific orientation parallel to the laser scan line, adding fixturing costs to the overall system.

More than Just Machine Vision
As other industries adopt automated imaging technologies, engineers often combine machine vision with other technologies to address the specific needs of an high-volume application or industry, as illustrated by the growth of 3D machine vision in gaming and entertainment and automotive safety systems, and now 2D auto-ID systems.

In the case of our VITRONIC’s VICAM^snap!, the system offers both audible and LED-based read confirmation, realizing that manual operations in noisy environments may require visual feedback without the cost of a computer display. Other systems include new cutting-edge variable focal depth optics that give the system greater depth of field for processing packages of varying sizes on a single line and even more unique system on chip approaches to speed system throughput.

When you take into account all the costs of an auto-ID application – acquisition cost, operations, manual labor support, and maintenance – customers quickly understand that image based auto-ID systems can match or beat laser-based scanning systems, while offering a future proof solution that can accommodate more complex 2D codes.