# Data matrix code quality verification

## Data matrix code quality verification

In this post I will write about main 4 criterion for evaluating Data matrix code quality. In accordance with ISO/IEC 15416 four criterion should be taken into consideration, which vary from A to F grade (A meaning very god and F meaning barely readable).

The readability of data matrix codes can be improved by optimizing the illumination. Main two aspects of optimization are type of light as well as illumination direction. Proposed types of light color are red light, blue light or UV lamp.

Symbol contrast

Symbol contrast refers to difference in dark and bright elements in data matrix code. Black cells on white surface represents 100% contrast. Inverting the bright and dark elements does not make any change. With bigger contrast the readability is increased.

 Contrast % Grade SC => 70 A (4.0) SC => 70 B (3.0) SC => 70 C (2.0) SC => 40 D (1.0) SC => 20 F (0.0)

Cell size ( Print Growth )

The actual print growth may differ from intended element size due to printing method itself.  Cell size may get bigger or smaller depending on ink bleed or lack of ink. The assessment becomes worse if deviation increases.

 Contrast % Grade -0.5 <= D <= 0.5 A (4.0) -0.7 <= D <= 0.7 B (3.0) -0.85 <= D <= 0.85 C (2.0) -1.0 <= D <= 1.0 D (1.0) D < -1.0 or D > 1.0 F (0.0)

Axial Non uniformity

Axial Non-Uniformity reflects the deviation that occurs between DMC main two axes. If the symbol with the same number of rows and columns is not square the certain amount of axial Non-Uniformity was introduced. In example it is obvious that one axis is greater than another.

 Contrast % Grade AN <= 0.06 A (4.0) AN <= 0.08 B (3.0) AN <= 0.10 C (2.0) AN <= 0.12 D (1.0) AN <= 0.12 F (0.0)

Unused error correction

Extra error correction code is encoded to Data matrix code, so even damaged labels can be read. One of the quality parameters is also the percentage of error correction code that had to be used in order to correctly decode data matrix code.

 Contrast % Grade UEC >= 0.62 A (4.0) UEC >= 0.50 B (3.0) UEC >= 0.37 C (2.0) UEC >= 0.25 D (1.0) UEC <= 0.25 F (0.0)

Overall quality of data matrix code cen be represented as maximum grade (A,B,C…) from all categories.