QR code detection and recognition in industrial production environment based on SSD and image processing

Xiong, Jianqiao; Zhou, Linli

doi:10.1117/12.3011655

Cited by 1 publication

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Two-dimensional barcodes have found extensive application across multiple sectors, including but not limited to electronic payments, the Internet of Things, healthcare, and transportation [1][2][3]. They are prevalent in marketing, business tracking, and ticketing because of their cost-effectiveness and ease of use [4,5]. Nevertheless, challenges such as damage, obstructions, and poor lighting can hinder QR code recognition in complex environments, with such conditions impeding regular decoders from accurately reading QR codes, complicating information tracing efforts [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…They are prevalent in marketing, business tracking, and ticketing because of their cost-effectiveness and ease of use [4,5]. Nevertheless, challenges such as damage, obstructions, and poor lighting can hinder QR code recognition in complex environments, with such conditions impeding regular decoders from accurately reading QR codes, complicating information tracing efforts [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancement of Two-Dimensional Barcode Restoration Based on Recurrent Feature Reasoning and Structural Fusion Attention Mechanism

Yi,

Chen

2024

Electronics

View full text Add to dashboard Cite

In practical scenarios, such as in electronics, where barcodes on electronic component carriers often wear out, and in logistics, where package labels frequently get damaged, this type of damage makes the recognition of two-dimensional (2D) barcodes challenging. In this study, a new repair method was introduced for quick response (QR) and PDF417 codes. In addition, a structural fusion attention (SFA) mechanism with a recurrent feature reasoning network was integrated to enhance structural integrity and recognition rates. The proposed method significantly outperforms existing inpainting models in terms of accuracy and robustness, which is demonstrated by the custom dataset provided by the authors. Notably, the approach ensures near-perfect recognition rates despite extensive structural impairments. It achieves an accuracy of 98% for large-area PDF417 occlusions and maintains a recognition rate of 100% for QR codes with 75–90% structural damage. These findings highlight the exceptional ability of the proposed method to restore 2D barcodes impaired by diverse levels of structural occlusion.

show abstract