How to read damaged or blurry barcodes

app store

Barcodes are essential for industries like retail, logistics, and manufacturing, which involve long-distance transport, multiple reloads, and highly variable environmental conditions. All this can affect barcode labels, making them hard to read with traditional scanning devices.

Let’s take a look at common problems you’re likely to encounter when working with barcodes – and at what you can do to overcome them.

💡 We’ve included various examples of damaged barcodes in this article. You’re welcome to use our free Barcode Scanning Demo App to try scanning them.

Common problems with barcodes

Ripped barcodes

Example of a ripped barcode

Rough handling can lead to a part of a barcode label being ripped off. This doesn’t necessarily make it unreadable, however: The data in a 1D barcode (e.g., UPC, EAN, Code 93, or GS1 DataBar) is encoded in the width of the black bars and the white space in between, not in their height (with some exceptions). So, as long as the remainder of the label has all the bars in an unbroken line, you can still read it with a good barcode scanner.

However, if a barcode is ripped vertically, no barcode scanner will be able to recover the data. Therefore, it’s best to prepare for this scenario in advance, e.g., by attaching multiple copies of the same barcode. It may also be worth switching to a 2D barcode, since two-dimensional symbologies like QR and Data Matrix have a much higher error tolerance.

Worn, dirty, or scratched barcodes

Example of a worn barcode

Dirt, wear, or scratches on a barcode label are less of a problem for barcode scanning software, but might pose a problem to laser scanners. We trained our Barcode Scanner SDK using computer vision algorithms and machine learning models to check for discrepancies in the barcode’s line sequence and restore any damaged parts. In most cases, this enables it to read the encoded data without issues.

Poorly printed or blurry barcodes

Example of a blurry barcode

Bad print quality greatly reduces a barcode label’s readability. Therefore, using a label printer specifically made for barcodes is crucial. 

However, should you encounter poorly printed barcode labels, modern scanning technology can go a long way in helping you read them. Thanks to the machine learning model powering our SDK, printing artifacts and washed-out lines don’t stand in the way of accurate scanning results.

But what if you need to scan a barcode from a blurry photograph? Here, too, powerful barcode scanning software can compensate, allowing you to read the barcode’s data correctly.

Extract 1D and 2D barcodes in milliseconds

Automating ineffcient and time-consuming workflows boosts productivity and reduces costs.
Barcodes make the transition seamless and can be scanned by any mobile device with a camera and the right software.

Our Barcode Scanner SDK can be integrated into your mobile or web app in just a few hours to transform any mobile device into a powerful barcode scanner!

Very small or distant barcodes

Example of a very small barcode

Sometimes the problem is not the barcode label’s quality – what if a barcode is just too small or too far away?

Our Barcode Scanner SDK has two special scanning modes to deal with these problems: One lets you zoom in on distant barcodes. The other uses a locked camera focus to help you scan very small barcode symbologies like Micro QR. The former is especially important for warehousing and other use cases where the labeled items are not easily accessible. Fixed-focus scanning, on the other hand, is useful when scanning tiny labels, such as those on lab sample tubes.

Curved barcodes and difficult angles

Example of a distorted barcode
Example of a angled barcode
Example of a barcode scanned from a poor angle

Another common issue involves barcodes that can only be scanned from an angle or that are printed onto curved surfaces. They are challenging to read for traditional laser scanners, since the light doesn’t bounce off them correctly.

Mobile barcode scanning software using computer vision, on the other hand, can detect which areas of a barcode are least distorted to accurately read the data.

Barcodes in poor lighting conditions

Example of a poorly lit barcode

Barcode scanners rely on the contrast between the black lines and the white space in between, so poor lighting can severely affect a code’s readability. With smartphone-based scanners, you can use the built-in flashlight, although this can produce glare. That’s why your scanning software should be able to handle low-contrast barcodes as well.

When our Barcode Scanner SDK detects a poorly lit 1D barcode it cannot read, its machine learning model applies a binarization filter to enhance the contrast and tries to scan the barcode once more. For 2D barcodes, our algorithms can work around the poor lighting conditions even without binarization.

How you can read barcodes in all conditions

All the issues mentioned above are quite common when working with barcodes. Thankfully, modern scanning software handle them with ease.

Based on our many years of experience working with enterprises that use our barcode technology on a daily basis, we have outfitted our Barcode Scanner SDK with specialized modules for scanning barcodes in any condition.

The SDK’s computer vision capabilities have been optimized using machine-learning algorithms, ensuring accurate reads even from scratched, distorted, poorly printed, or blurry barcodes.

See for yourself by trying out our free Barcode Scanning Demo App – or contact our solution experts so we can discuss your individual use case. We also offer a free 7-day trial, so you can get started with the integration into your mobile or web app right away.

Developers, ready to get started?

Adding our free trial to your app is easy. Download the Scanbot SDK now and discover the power of mobile data capture