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DataMatrix Code Recognition Method Based on Coarse Positioning of Images

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Bibliographic Details
Title: DataMatrix Code Recognition Method Based on Coarse Positioning of Images
Authors: Lingyue Hu, Guanbin Zhong, Zhiwei Chen, Zhong Chen
Source: Electronics. 14:2395
Publisher Information: MDPI AG, 2025.
Publication Year: 2025
Description: A DataMatrix (DM) code is an automatic identification barcode based on a combination of coding and image processing. Traditional DM code sampling methods are mostly based on simple segmentation and sampling of a DM code. However, the obtained DM code images often have problems such as wear, corrosion, geometric distortion, and strong background interference in practical scenarios. To improve decoding ability in complex environments, a DM code recognition method based on coarse positioning of images is proposed. The two-dimensional barcode is first converted into a one-dimensional waveform using a projection algorithm. Then, the spacing between segmentation lines is predicted and corrected using an exponential weighted moving average model for adaptive grid division. Finally, the local outlier factor algorithm and local weighted linear regression algorithm are applied to predict and binarize the gray level values, converting the DM code image into a data matrix. The experimental results show that this method effectively handles problems like blurring, wear, corrosion, distortion, and background interference. Compared to popular DM decoding libraries like libdmtx and zxing, it demonstrates better resolution, noise resistance, and distortion tolerance.
Document Type: Article
Language: English
ISSN: 2079-9292
DOI: 10.3390/electronics14122395
Rights: CC BY
Accession Number: edsair.doi...........20a07f17e23caac325f3aa308c1ebbcc
Database: OpenAIRE
Description
Abstract:A DataMatrix (DM) code is an automatic identification barcode based on a combination of coding and image processing. Traditional DM code sampling methods are mostly based on simple segmentation and sampling of a DM code. However, the obtained DM code images often have problems such as wear, corrosion, geometric distortion, and strong background interference in practical scenarios. To improve decoding ability in complex environments, a DM code recognition method based on coarse positioning of images is proposed. The two-dimensional barcode is first converted into a one-dimensional waveform using a projection algorithm. Then, the spacing between segmentation lines is predicted and corrected using an exponential weighted moving average model for adaptive grid division. Finally, the local outlier factor algorithm and local weighted linear regression algorithm are applied to predict and binarize the gray level values, converting the DM code image into a data matrix. The experimental results show that this method effectively handles problems like blurring, wear, corrosion, distortion, and background interference. Compared to popular DM decoding libraries like libdmtx and zxing, it demonstrates better resolution, noise resistance, and distortion tolerance.
ISSN:20799292
DOI:10.3390/electronics14122395