Improving Version Detection for JAB Codes

The focus of the work is to improve the reading performance of JAB Codes. JAB Code is a polychrome barcode that is ISO standardized. The weakness of the standardized decoding algorithm is the very low reading performance of under 10% for very large and rectangular codes. In many IT security applications, however, large and rectangular codes are required for the huge payload. In this paper, we present three different methods to improve the decoder. These methods aim at determining the version size of the JAB Code to be read. This is the step after the JAB Code has been located by the finder patterns and before the decoding can take place. The three methods have their advantages and disadvantages in their accuracy and performance. The evaluation compares detection rates and error performance for Baseline, Segmentation, Zero Crossing, and Local Sampling methods. The results show that Local Sampling achieves the highest detection rates, with 285 partial and 131 complete detections, while also maintaining the lowest error levels. The other methods perform significantly worse. The findings highlight that Local Sampling offers the best performance, effectively addressing the challenges of version size determination with improved accuracy and reliability.