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A Guide to Barcode Basics and Symbology

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Overview

Barcodes are used across industries to identify and keep track of products by a label with a unique identifier. With barcodes, a centralized record can track information such as prices and stock levels, and that information can be changed without requiring printing new labels or tags.

Barcode patterns (lines and modules) provide a way for numeric or alphanumeric information to be read by an electronic scanner much more accurately and quickly than numbers and letters could.

Barcodes can be read by either laser (for 1D barcodes) or image scanners (for 1D or 2D barcodes), and in the case of 1D barcodes, require a database to store the information they contain.

Among the most common 1D barcode types are Code 128, which include Universal Product Codes (UPC). While 2D barcodes are not necessarily made up of "bars," they are still considered a type of barcode. 2D barcode types include PDF417, Data matrix, and QR Codes. RFID tags are not barcodes. More on that here.

Standards and common practice for barcodes have been moving in favor of 2D types, for reasons that will be covered more below. The international barcode standards organization, GS1, will be updating its standards for barcodes in their Sunrise 2027 initiative to transition to 2D barcodes. Learn more here.

1D vs 2D Barcodes

Components of Common Barcode Types:

common barcode components

Advantages of 2D Barcodes

2D codes can contain much more information than 1D barcodes.

  • 1D codes are read linearly; 2D codes can be read both horizontally and vertically, making it possible to store a high density of information in a small space.
  • 1D codes contain under 100 characters but are typically about 25 characters; 2D codes can contain up to 2,335 alphanumeric characters.
  • Because 2D barcodes have large storage capacity, they do not necessarily require a database to store the information they contain.

2D codes are easier to scan.

  • No matter how a 2D barcode is positioned (upside down, diagonal), it can still be read reliably at first pass.
  • 2D codes are designed to be read at lower resolution. In the case of a vision system such as our RaPTr (Rapid Pallet Tracker) system, this translates to inexpensive and/or fewer cameras. See the following section on Image vs Laser Scanning.

2D codes are more hard-wearing.

  • Because information is encoded in 2D barcodes with error-protection formulas, even damaged barcodes can still be read.

2D codes are smaller in label real estate while also appearing bigger to a camera.

  • A camera must be able to read the smallest element within a barcode: for a 1D barcode this is the narrow bar width and for a data matrix it is the module width. All the barcodes shown here encode the exact same information. The two first codes are shown at the same scale, and the narrow bar width on the 1D code and the module width on the 2D code are equal. To a human eye, it may appear that the 1D code is “bigger,” but to a camera, they are exactly the same. On the last barcode at right, the module width is doubled in size, making the module width twice as large to the camera while still taking up less real estate than the 1D code at left.
Size benefits of 2D vs 1D code

Image Scanning Vs Laser Scanning

While image scanners can read either 1D or 2D barcodes, laser scanners only read 1D codes. Technological improvements have made imaging scanners ever more cost-competitive with laser scanners.

2D imagers can not only read different types of barcodes, they can read them omnidirectionally, and from greater distances than most laser scanners. They can also more easily detect damaged and poorly printed barcodes. All of this contributes to improved scanning accuracy and speed.

Image scanning also provides the ability for capturing scanned images and storing them in a database for photographic reference and verification.

Optimizing Barcodes and Labels

The larger the module size of a 2D barcode, the easier it is to scan and the lower resolution required. This translates to fewer and less expensive cameras required to scan. The image at right shows a 14x14 module data matrix with a module size of 3mm. Artemis Vision recommends 14x14 data matrix as it allows an enormous number of unique data combinations.

Artemis Vision recommends only encoding the information to the data matrix that is minimally required for unique identification, as additional information requires more modules, requiring the module size to be smaller. For example, in pallet labeling, if adding 2D codes or switching to 2D codes from 1D codes, information from the entire label does not need to exist in the barcode. The unique, serialized number is the most important part (e.g. Serial Shipping Container Code (SSCC)). Find white space and unneccessary text on labels to create more room for barcodes. See next page for optimized label examples.

Artemis Vision’s systems can filter barcodes by type and content, so it is also not necessary to eliminate 1D codes if there is resistance to replacement. Incorporating an additional 2D code, whether to an existing label where space allows, or by additional label, is an acceptable solution for image scanning.

See the table which shows examples of the character capacity in a data matrix depending on the matrix size. (Up to 144x144 matrix size is possible.)

table showing data matrix capacity by size

Examples (warehouse)

The label below shows a data matrix with module size of 3mm on a 4x6in label, which is Artemis Vision’s recommended size for best performance.

The next label example shows an enlarged code containing only SSCC information alongside the smaller code at left that packs in more information.

example of shipping label optimized for vision scanning
Example of shipping label with enlarged datamatrix

The following pictures show 2D barcodes (highlighted in green) placed on pallets. On multi-stacked pallets the barcodes can be read simultaneously.

pallet with code scanned
double-stacked pallet with codes scanned

While both data matrix and QR 2D code types offer superior readability, data matrices tend to read even better than QR codes at angles and under plastic wrap:

RaPTr system side by side comparison reading datamatrix vs QR code

If you have any questions or requests for more detail, let us know.

Get a downloadable pdf version of this guide here.

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