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RECOGNITION OF DATA MATRIX CODES IN IMAGES AND THEIR APPLICATIONS IN PRODUCTION PROCESSES.

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Titel: RECOGNITION OF DATA MATRIX CODES IN IMAGES AND THEIR APPLICATIONS IN PRODUCTION PROCESSES.
Autoren: KARRACH, Ladislav, PIVARČIOVÁ, Elena
Quelle: Management Systems in Production Engineering; Sep2020, Vol. 28 Issue 3, p154-161, 8p
Schlagwörter: MANUFACTURING processes, ALGORITHMS, CIPHERS, MATRICES (Mathematics), VIDEO coding
Abstract: Data Matrix codes can be a significant factor in increasing productivity and efficiency in production processes. An important point in deploying Data Matrix codes is their recognition and decoding. In this paper is presented a computationally efficient algorithm for locating Data Matrix codes in the images. Image areas that may contain the Data Matrix code are to be identified firstly. To identify these areas, the thresholding, connected components labelling and examining outer bounding-box of the continuous regions is used. Subsequently, to determine the boundaries of the Data Matrix code more precisely, we work with the difference of adjacent projections around the Finder Pattern. The dimensions of the Data Matrix code are determined by analyzing the local extremes around the Timing Pattern. We verified the proposed method on a testing set of synthetic and real scene images and compared it with the results of other open-source and commercial solutions. The proposed method has achieved better results than competitive commercial solutions. [ABSTRACT FROM AUTHOR]
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Abstract:Data Matrix codes can be a significant factor in increasing productivity and efficiency in production processes. An important point in deploying Data Matrix codes is their recognition and decoding. In this paper is presented a computationally efficient algorithm for locating Data Matrix codes in the images. Image areas that may contain the Data Matrix code are to be identified firstly. To identify these areas, the thresholding, connected components labelling and examining outer bounding-box of the continuous regions is used. Subsequently, to determine the boundaries of the Data Matrix code more precisely, we work with the difference of adjacent projections around the Finder Pattern. The dimensions of the Data Matrix code are determined by analyzing the local extremes around the Timing Pattern. We verified the proposed method on a testing set of synthetic and real scene images and compared it with the results of other open-source and commercial solutions. The proposed method has achieved better results than competitive commercial solutions. [ABSTRACT FROM AUTHOR]
ISSN:22990461
DOI:10.2478/mspe-2020-0023