Ber Based FRR Analysis of Low Parameter Grade 2D Barcodes

Abstract

The recent popularity of camera equipped mobile phones has introduced a new field for use of 2D bar codes. A code can be printed on everyday items and be interacted with using a camera phone. 2D bar codes were designed to carry significantly more data with higher Information density and robustness than its 1D counterpart. A two dimensional bar code contains binary and alphanumeric information, which is decoded by camera equipped mobile phones. Data entry for mobile phones has always been limited by the phone’s numeric keypad. One way to overcome this is through 2D barcodes read by the phone’s camera. Bar code reading applications use phone’s camera to capture an image of bar code and then use the phone’s processor for decoding. My thesis reviews the causes of low parameter grade in Data matrix 2D barcodes and suggests the image processing techniques to improve BER performance for low parameter grade 2D barcodes. Previous related work in this field is also presented in literature survey. 2D Barcode symbol grade is the most important parameter for communicating the print quality of a symbol. The scan grade is the lowest grade achieved for parameters Symbol contrast, Modulation, Fixed Pattern Damage, Axial non-uniformity, Grid non-uniformity, Angle of distortion. I have considered the fidelity of the camera phone’s captured image as a metric for gauging reading reliability. Bit Error Rate (BER) is used as an indicator for having a good First Read Rate (FRR). First Read Rate is an advanced and better gauge for bar code reading reliability. The aim of thesis is to improve this BER by applying known image processing based algorithms on individual parameter prone low-grade bar codes to help increasing the FRR. In this thesis, I set up test experiments for same low-grade barcodes, which will be enhanced using image processing techniques using Matlab.