Author
Listed:
- Dung D. Vo
(Department of Industrial Electronic - Biomedical Engineering, Faculty of Electrical - Electronics Engineering, HCMC University of Technology and Education, Vietnam)
- Duy T. Nguyen
(Department of Industrial Electronic - Biomedical Engineering, Faculty of Electrical - Electronics Engineering, HCMC University of Technology and Education, Vietnam)
- Hai Thanh Nguyen
(Department of Industrial Electronic - Biomedical Engineering, Faculty of Electrical - Electronics Engineering, HCMC University of Technology and Education, Vietnam)
- Viet B. Ngo
(Department of Industrial Electronic - Biomedical Engineering, Faculty of Electrical - Electronics Engineering, HCMC University of Technology and Education, Vietnam)
Abstract
Barcode attached on product is to transfer information to users. In practice, many barcodes are degraded over time and they are difficult for users to recognize product information. Therefore, barcode image restoration plays an important role due to clearly showing product information for users. This paper proposed a restoration approach of barcode- EAN 13 images with different degraded characteristics such as vertical lines, blurring, dashed lines. In particular, the degraded barcode images are pre-processed for restoring before recognition, in which a radon method is applied for rotating barcode image and an Otsu segmentation method is employed to split the barcode image from an original image. Therefore, bars in each barcode image are determined for recognition of the correct barcode. Barcode image datasets are collected from different practical products with different quality for restoration before recognizing them. Experimental results show to illustrate the proposed approach for the barcode recognition is the effectiveness
Suggested Citation
Dung D. Vo & Duy T. Nguyen & Hai Thanh Nguyen & Viet B. Ngo, 2019.
"Barcode Image Restoration for Recognition of Product Information,"
European Journal of Engineering and Technology Research, European Open Science, vol. 4(9), pages 93-100, September.
Handle:
RePEc:epw:ejeng0:v:4:y:2019:i:9:id:61522
DOI: 10.24018/ejeng.2019.4.9.1522
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