Title
Agent-based two-dimensional barcode decoding robust against non-uniform geometric distortion
Abstract
Two-dimensional (2D) codes are assumed to be printed on flat planes and subject to distortion when printed on non-rigid materials such as papers and clothes. Although general 2D code decoders correct uniform distortion such as perspective distortion, it is difficult to correct non-uniform and irregular distortion of 2D code itself. To cope with this problem, this paper proposes an agent-based approach to reconstruct 2D code. In this approach, auxiliary lines are given to a 2D code and used to recognize the distortion. First, the proposed method finds 2D code area using feature patterns composed by the auxiliary lines, and looks for finder patterns by Convolutional Neural Network (CNN). Then, many agents simultaneously trace the lines referring various image features and neighborhood agents. Feature weights are optimized by Genetic Algorithm. Experimental results showed that the proposed method has prospects that it can decode distorted 2D code without occlusion.
Year
DOI
Venue
2015
10.1109/SOCPAR.2015.7492804
2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR)
Keywords
Field
DocType
Two-dimensional barcode,Image rectification,Convolutional neural network,Multi-agent system,Genetic algorithm
Perspective distortion,Pattern recognition,Convolutional neural network,Computer science,Image rectification,Feature (computer vision),Artificial intelligence,Decoding methods,Barcode,Distortion,Genetic algorithm,Machine learning
Conference
ISSN
Citations 
PageRank 
2381-7542
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Kazuya Nakamura100.68
hiroshi kawasaki227450.85
Satoshi Ono321939.83