Data Matrix is a type of 2-D barcode with very high data density and can encode a large amount of data. Data Matrix consists of a random sequence of black and white pairs. Data matrix code type can encode the text, as well as raw data. The range of the data encoded by the Data matrix usually lies between a few bytes up to 2 kilobytes. With this data storage space, approximately 2,335 alphanumeric characters can be encoded by a data matrix symbol. Data Matrix coding standard is widely used in Europe and the United States for information encoding.
ID Matrix is credited as being the inventor of the Data Matrix barcode around 2005. ID Matrix, later on, merged into RVSI Acuity ciMatrix, Siemens Energy and automation acquired RVSI Acuity ciMatrix in October 2005 and then by Microscan Systems in September 2008.
Data Matrix is a two-dimensional symbology hence appears in two basic shapes. Either a square between the sizes of 10×10 up to 144×144 modules in even steps or a rectangle between the size of 8×16 up to 16×48.
The size and shape of the symbol are usually chosen either automatically or by the user. Often, the smallest size is preferred, so there is enough data to encode the given data. The symbol rectangle is built up by square dots whose size module is also user-specified. A Data Matrix can even be small enough to fit on a pinhead!
The symbol is mounted on a square grid, that has a finder pattern encompassing the edges of the symbol to allow a scanner to identify the barcode. The finder pattern makes it possible to read the barcode regardless of the physical orientation of the code.
Like other 2-D barcodes, the basic purpose of developing the Data Matrix code type was to design a barcode that is denser and can accommodate a large amount of data, which is extremely secure with built-in error correction and higher fault tolerance mechanism. All of these objectives have been met by the Data Matrix bar code and incorporated into the design.
The most widespread use for Data Matrix is labeling small items, due to the code’s ability to encode fifty characters in a graphic symbol at 2 or 3 millimeters. Additionally, the code can be read with an estimated 20% contrast ratio. It is no wonder that Data Matrix codes are often used in the food industry in autoencoding systems to prevent food products from being packaged and dated incorrectly.
These unique codes are managed internally on a food manufacturer’s database and used for each subsequent product run. The symbol should be in an optimal scanning position. Other industries that use Data Matrix include the manufacturing of pharmaceutical items, electronics, and medical devices.
There is only one major limitation of Data Matrix barcodes. Users have to have a laser scanner or CCD cameras in order to correctly scan and encode information stored in these barcodes, it cannot be scanned by a simple scanner. Factors affecting data matrix imagers can also cause limitations. Imagers regularly require that the barcode is close to the lens. Generally, distance considerations should be in the 2-12″ range. However, exceptional lensing can increase this range. Some linear barcode scanners can accurately decode at intervals up to 120″.
Due to a large amount of processed information, data matrix imagers cannot decode at the same rates as linear barcode scanners. Also, while most imagers contain internal light sources to illuminate the barcode, they may function at subpar levels because of shallow contrast, specular reflection, or causes for image blur.
The most widespread use for Data Matrix is labeling small items, due to the code’s ability to encode fifty characters in a graphic symbol at 2 or 3 millimeters. Additionally, the code can be read with only a 20% contrast ratio. It is no wonder that Data Matrix codes are often used in the food industry in autoencoding systems to prevent food products from being packaged and dated incorrectly.
These unique codes are managed internally on a food manufacturer’s database and used for each subsequent product run. The symbol should be in an optimal scanning position. Other facts about data matrix usage include the following:
In general, there are two categories of a data matrix, which are the Data Matrix ECC 000-140 and Data Matrix ECC 200.
Data Matrix ECC 000 to 140 are considered the older versions. All these versions have error correction systems based on convolution. In addition, each of these versions offers a different error correction capacity. However, ECC 000 provides no error correction, while ECC 140 offers the most correction. A CRC (cyclic redundancy check) is encoded on each bit pattern so that error detection can be conducted during decoding. Similarly, tables containing bit-placement instructions are used to encode each bit. In addition, the modules of these data matrixes are always odd.
ECC 200 offers users a newer version of a data matrix. Unlike the older version, the ECC 200 conducts erasure recovery and error correction using Reed-Solomon codes. Therefore, the data stored within can be accurately encoded if damage to the data matrix does not exceed 30%. Therefore, the ECC 200 has a significant advantage over the older versions.
A data matrix and a QR code are both used to store information. Each technology offers a simple yet effective way of transmitting data. However, there are several similarities and differences between these tools.
The Data Matrix and QR code are both 2-dimensional barcodes. Information can be stored in any of these technologies vertically and horizontally in pixels. As such, a lot of information can be stored within either of these technologies. Likewise, either of these codes can be read by a scanner in different directions. Also, damage to these 2-D barcodes does not prevent access to the stored information.
Although a data matrix and a QR code are similar, there are several differences between them. Presented below are some of these differences.
On the other hand, the QR code has 4 black and white squares at every corner. This structure can store a maximum alphanumeric character of 4196. However, 7089 numeric characters can be stored in a numeric combination when required. Therefore, the large storage capacity of a QR code makes it suitable for use on large items. Similarly, it is easier to read with a smartphone or barcode scanner.
The QR code has a different error correction level setting. The value can be manually selected when encoding information on the barcode. However, the higher the percentage, the less storage available.
Data Matrix codes are considered the smallest and most compact of all the bar code types. If you want to store a large amount of data in a barcode, Data Matrix is the most recommended barcode type. It can be easily generated with Bytescout BarCode SDK and read with BarCode Reader SDK.