An Evaluation of 2D Barcodes in Document Processing Applications


Many reports that are to be electronically handled contain scanner tags to encode significant data that is extricated through standardized identification disentangle programming. There are various issues that ought to be thought about while picking a standardized identification symbology. The biggest distinctive trademark to be considered is whether a direct (1D) or 2 Dimensional (2D) symbology is to be utilized. 1D symbologies, as the name suggests, commonly comprise of width balanced bars and spaces that encode the client data. There is no data contained in the upward element of a 1D image. 2D symbologies encode data in the two elements of the image and accordingly, have a lot higher information thickness. 2D images commonly utilize a standard lattice of conceivable cell positions, where a cell is either dark or white.

This article will zero in on the utilization of 2D images in report handling applications in light of the huge information thickness benefit of 2D images over 1D images. Specifically, we will analyze the overall benefits of three famous public area 2D symbologies: Data Matrix, QR Code and Micro QR Code. Following a short outline of every symbology, we will look at them in view of their information thickness, mistake rectification, and relative handling speed.

Information Matrix

Information Matrix images utilize an ordinary cluster of square cells running in size from a 10 by 10 lattice up to a 144 by 144 framework. A 1 cell calm zone is expected around the whole image. What’s more, rectangular sizes are additionally accessible. Every image comprises of a fixed “L” design that is utilized for finding alongside a clock track along the contrary sides of the “L”. What’s more, there are inside clock tracks for bigger Data Matrix. These proper areas encode no data. They are available to recognize the image as a Data Matrix and to help the unravel programming. The excess matrix areas contain either a dark or white squares relying upon the data to be encoded.

QR Code

QR Code images likewise utilize an ordinary cluster of square cells running in size from a 21 by 21 network up to a 177 by 177 matrix. A 4 cell calm zone is expected around the whole image. To help finding, QR Code images contain 3 locater designs at 3 of the 4 corners. Also, there are interior arrangement designs, clock designs, as well as configuration data on bigger images that gives the size of the code.

For information applications that require more modest measures of information, there is a subsidiary rendition of QR Code called Micro QR Code which can encode up to 35 numeric digits in less space than a relating QR Code. It has 4 different square sizes: 11 by 11, 13 by 13, 15 by 15 and 17 x 17. Each size requires a 2 cell calm zone around the whole image. It contains just 1 locater design, with restricted clock example and configuration data.

Information Density and Error Correction

Information Matrix has an unmistakable information thickness advantage over QR Code. This is particularly valid for more modest measures of client information. This is because of the way that it has less fixed cell areas. enterprise automation It doesn’t commit as much space for locater designs, and contains no arrangement data. Miniature QR Code was intended to address the information thickness issue and is practically identical in size to the Data Matrix for this information content.

Each of the 3 sorts of images use Reed Solomon blunder rectification to distinguish and address mistakes because of image harm or imaging issues. The quantity of perceptible and correctable not entirely settled by the quantity of additional mistake adjustment codewords remembered for the image that are well beyond the codewords used to encode the information.

The information limit of a given size image is an element of how much blunder revision above as well as the actual information. Information Matrix utilizes a decent degree of blunder rectification that isn’t selectable by the client. The level of blunder remedy codeword above goes from 62.5% for the littlest image down to 28% for bigger images. Paradoxically, QR Code has 4 distinct degrees of mistake amendment that permit an estimated recuperation limit of 7%, 15%, 25% or 30%. Miniature QR Code changes the decisions of how much mistake amendment for every one of the 4 passable sizes. The littlest just permits mistake discovery, while the biggest permits up to 25% recuperation limit.

The sum and sort of client information will direct the size of the image that is fundamental. What’s more, for QR Code and Micro QR Code, how much blunder rectification utilized will factor into the size too. The table underneath sums up the overall size and mistake rectification limits of the 3 images displayed previously.

Symbology – – Relative Size

(with Quiet Zone)/Error Correction Overhead (%)/Maximum Correctable Errors

Information Matrix – – 1.00/58.3/3

QR Code – – 3.70/65.3/8

Miniature QR Code – – 1.33/50.0/1

The decision of how much blunder remedy utilized in QR Code and Micro QR Code is application subordinate. In circumstances where size is an issue, one might be enticed to lessen how much blunder rectification above. This might decrease the general read pace of the image if the scanner tag might be harmed or on the other hand assuming the imaging climate makes it more hard to get “ideal” pictures. Standardized tags on delicate bundles that bend the image, as well as sparkly tape over the image that can cause specular reflection back to the camera are instances of how codes might be harmed. By and large, in the event that space grants, for ideal read rates, one ought to ordinarily pick the most extreme permissible mistake remedy limit.

Relative Processing Speed

Progressively applications where an opportunity to unravel a picture is significant, one must likewise think about the symbologies on how rapidly they can be decoded. The most tedious piece of unraveling a standardized identification inside a huge and occupied picture is by and large tracking down the image. The more exceptional the locater design inside a standardized identification image, the simpler it is to situate inside a bustling picture. This lessens handling time. On the other hand, if a standardized tag symbology doesn’t give an extraordinary locater design, additional time will be spent searching for it.

QR Code and Micro QR code enjoy a critical upper hand over Data Matrix due to the exceptional locater designs inside the images. QR Code is awesome of the 3 decisions since it incorporates 3 locater designs, each having the option to be utilized to track down the image. Information Matrix has the “L” locater design and fixed clock lines. Sadly, these are not awfully special examples with structures where numerous areas of text are encircled by boxes. Likewise, both QR (Version 7 or more) and Micro QR Codes include design data inside the image to tell you the size of the image and to affirm you are on a genuine image. Information Matrix doesn’t contain unequivocal organization information, giving just a clock track on the contrary sides of the image from the “L” corner.

A bustling structure was checked at 200 DPI, and a solitary occasion of the 3 standardized tag images was added to the picture with every image utilizing 25 mil cells. Then, at that point, in 3 separate passes, Volo(TM), a standardized identification unravel programming tool stash from Omniplanar®, was utilized to translate every image. In each pass, just a single symbology type was empowered. The table underneath sums up what amount of time it required for Volo to issue the translate result and totally wrap up handling the picture. Both QR Code and Micro QR disentangling were 3 to multiple times quicker than Data Matrix translating. This is primarily because of the great locater design in the QR and Micro QR images.