ALGORITHMIC PROVISION OF ERROR-CORRECTING MULTI-COLORED BARCODE PATTERNS BASED ON GF(p)

Abstract

Background. In recent years, there has been a steady trend towards the using of multi-colored barcodes. This increases the information density of the data compared to black and white barcodes. However, this complicates the processes of recognition and decoding of bar code images. Therefore, in order to reliably read multi-colored barcodes from an object, it is necessary to ensure noise immunity of bar code patterns – the minimum structural units of the bar code image. Objective. The purpose of the paper is development of a method for the synthesis of symbolics of multi-colored bar codes, which have the property of noise immunity at the level of bar code patterns. Methods. This goal is achieved through the using of multivalued incomplete Hemming codes as the basis for constructing bar code patterns. The numerical equivalent of the bar code pattern is a code word of the multi-valued Hemming code, in which the encoding-decoding operations are performed according to the rules of a finite field GF(p). Results. A number of error-correcting multi-colored barcodes have been proposed, in which one-time distorted element (error) is corrected at the level of barcode pattern and a significant number of multiple distortions are detected. The error-correcting capability of multi-colored barcode patterns has been evaluated. Conclusions. The proposed method of the synthesis of symbolics of multi-colored barcodes allows creating barcodes with improved error-correcting characteristics, which provides the appropriate level of reliability of the process of reading multi-colored barcodes in automatic identification systems.