In the consumer-electronics repair industry, it is often required to track data on high volumes of consumer premised equipment. The most important tracking data are often printed on the units in the form of labels using 1D and 2D barcodes and textual data. It is a common requirement to record all of the data stored on the label before beginning the refurbishment process, since the label should be reproducible (in case of damage to the label itself, hardware or software upgrades that modify the data, or simply because the label was functioning as a seal). These tasks are usually performed manually using a handheld barcode-scanner, which has certain financial drawbacks as well as the possibility of human error. Handheld laser scanners are prone to deny processing the barcode in case of worn, or damaged labels, and only a few models are able to process QR codes. The two main quality indicators of information systems dealing with recording label data are the human labor cost the system requires from the user and the quality of the recorded data. In my thesis I am willing to develop an image processing system which aims to improve the recording process by both of these measures.