Understanding Barcode Verification Results

Barcode verifiers grade the quality of codes based on a list of quality parameters and generate official quality reports. The software is not designed to tell a user to change an ink cartridge or printing needle, so the information requires interpretation. A basic understanding of how barcodes are decoded and what quality parameters measure can help you get the most out of your verification process.

Grading Process

The first step for all verifiers is to determine whether the code can be decoded by the standard reference decode algorithm. This is a way to essentially guarantee that even the most rudimentary barcode readers should be able to decode the symbol. If a code cannot be decoded, the verifier will show an “F” grade and state “NO DECODE.” This is different from how a failing code that has been decoded would be displayed. A code that receives an “F” grade but passed the decode process would show a grade for each of the quality parameters.

Once a barcode passes decode, it will then be assessed by the following parameters:

• Symbol contrast or cell contrast (if it is a DPM code)
• Modulation
• Reflectance margin
• Fixed pattern damage
• Axial non-uniformity
• Grid non-uniformity
• Unused error correction.

The lowest grade received will then become the overall grade for the code. For example, if the results show an “A” for every parameter but a “B” is given for axial non-uniformity, the grade for that barcode will be a “B.”

Modulation

Modulation is one of the most common causes for a reduction in barcode quality. Modulation refers to localized issues with contrast, meaning that certain spots within a code are not displaying enough contrast. This is different from symbol contrast, where the entire code suffers from low contrast. The verification software should highlight the problematic cells. A high-quality barcode has well-defined dark and light cells. During the decode process, cells that are labeled as a shade of grey will be converted to either a black or white module based on the software’s calculation when the image is changed to a binary image. This leaves room for error; cells can be mis-labeled, causing error correction to be applied.

Since the software highlight which cells have issues with modulation, focus on identifying what’s causing the modulation. The first place to look is at bar width growth (also known as print growth). Growth can be caused by using too much or too little ink, the type of paper, laser speed, heat levels, or focus. A quick way to identify growth is to look at the proportion of the dark cells to the light cells. They should be the same size. If one is much larger than the other, there is a growth problem. The software will provide you with an exact growth percentage for both horizontal and vertical directions. That information can be used to adjust artwork, ink flow, laser settings, etc.

If the bar width growth levels are only slightly off, the next place to look is the modulation value table. This will tell you how close the cell falls to the global threshold. The cells with modulation values that are marked in yellow or red should be examined to see if they need to be made darker or lighter to be more consistent with their like modules. If a cell value within the data and not the finder pattern lands directly on the global threshold, it will have a zero-value listed. Other causes for issues with modulation could be the substrate used, or even the size of the aperture. Typically, there is a specific aperture size called out in each industry’s application standard. It’s important to use the recommended size, or results can be skewed.

Common issues and solutions

Marking speed and intensity as well as ink amount and paper type are some of the most common things affecting quality. The below chart provides possible solutions to help improve the listed quality parameter.

To learn more about understanding verification results, watch the free on-demand webinar Understanding Barcode Verification Results.