A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques
| Autor: | Biao Hu, Junnian Li, Zhengcai Cao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies Deblurring business.industry Computer science Motion blur ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Binary number 02 engineering and technology 010501 environmental sciences 01 natural sciences Thresholding Motion (physics) Image (mathematics) Code (cryptography) Computer vision Artificial intelligence business 0105 earth and related environmental sciences |
| Zdroj: | CASE |
| Popis: | Quick Response (QR) Code would be easily affected by motion blur. In this study, a new recognition method for blurry QR Code is presented. First, a motion deblurring algorithm based on generative adversarial networks (GAN) is applied to perform the blind motion deblurring on single QR Code image for improving the quality of QR Code pictures. Then a modified local adaptive thresholding algorithm applying integral image technology is utilized in order to acquire binary QR Code pictures. Finally, this algorithm would be compared with some previous methods. Furthermore, for testing this algorithm, a database which contains motion blurry QR Code images from both public database and real scenes is collected. Experimental results show that this proposed algorithm perform well on motion blurry QR Code recognition missions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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