رفع اعوجاج و بازسازي كد هاي QR ناخوانا با استفاده از شبكه‌ي عصبي عميق

Reconstruction of illegible QR codes using deep neural network

اﻣﺮوزه ﺑﺎرﮐﺪ ﻫﺎ ﻧﻘﺶ ﭘﺮرﻧﮕﯽ در ﺻﻨﺎﯾﻊ ﻣﺨﺘﻠﻒ اﯾﻔﺎ ﻣﯽﮐﻨﻨﺪ و در ﺑﯿﻦ ﺑﺎرﮐﺪ ﻫﺎي دوﺑﻌﺪي ﻣﻌـﺮوف ﺗـﺮﯾﻦ آن ﻫـﺎ ﯾﻌﻨـﯽ ﮐـﺪ QR )ﮐـﺪ ﭘﺎﺳﺦ ﺳﺮﯾﻊ( رﺷﺪ روز اﻓﺰوﻧﯽ داﺷﺘﻪ اﺳﺖ. ﻫﺪف اﺻﻠﯽ اﯾـﻦ ﻣﻘﺎﻟـﻪ اراﺋـﻪ ي روش رﻓـﻊ ﻧـﻮﯾﺰ ﻣﺒﺘﻨـﯽ ﺑـﺮ ﺷـﺒﮑﻪ ي ﻋﺼـﺒﯽ ﻋﻤﯿـﻖ ﺧـﻮد ﺷﻨﺎس اﺳﺖ ﮐﻪ ﺑﺎ اﺳﺘﻔﺎده از آن ﺑﺘﻮان QR ﻫﺎي ﻣﺨﺪوش ﻏﯿﺮ ﺧﻮاﻧﺎ را دوﺑﺎره ﺑﻪ ﺣﺎﻟﺖ ﺧﻮاﻧﺎ ﺑﺎزﮔﺮداﻧﺪ. ﺑﺮاي اﯾﺠﺎد ﻧـﻮﯾﺰ و اﻋﻮﺟـﺎج ﺑـﺮ ﺧـﻼف ﻣﻘـﺎﻻت دﯾﮕـﺮ ﮐـﻪ از ﺷـﺒﯿﻪ ﻧـﻮﯾﺰ اﺳـﺘﻔﺎده و آن را ﺑـﻪ ﺗﺼـﻮﯾﺮ اﺿـﺎﻓﻪ ﮐﺮدﻧـﺪ ، از ﭼـﺎﻟﺶ اﺳﺘﺨﺮاج QR ﻧﻬﺎن ﻧﮕﺎري ﺷﺪه درون ﯾﮏ ﺗﺼﻮﯾﺮ رﻧﮕﯽ اﺳﺘﻔﺎده ﺷﺪه ﺗﺎ ﺑﺎ ﺟﻤﻊ آوري داده ﻫﺎﯾﯽ از ﺟﻬﺎن واﻗﻌﯽ ، ارزﯾـﺎﺑﯽ ﺟـﺎﻣﻊ ﺗـﺮ و واﻗﻌﯽ ﺗﺮي از ﮐﯿﻔﯿﺖ و ﺧﻮاﻧﺎﯾﯽ QR ﻫﺎي رﻓﻊ ﻧﻮﯾﺰ ﺷﺪه ﺑﺎ روش اراﺋﻪ ﺷﺪه را داﺷـﺘﻪ ﺑﺎﺷـﯿﻢ. در ﻧﺘﯿﺠـﻪ دﯾﺘـﺎ ﺳـﺖ ﺟـﺎﻣﻌﯽ از QR ﻫﺎي ﻣﺨﺪوش ﺣﺎﺻﻞ از ﺳﻪ روﯾﮑﺮد اﺳﺘﺨﺮاج ﻧﻬﺎن ﻧﮕﺎره ﻣﺘﻔﺎوت ﺑﻌﺪ از ﺣﻤﻠﻪ ي اﺳﮑﺮﯾﻦ-دورﺑـﯿﻦ را اﯾﺠـﺎد ﻧﻤـﻮدﯾﻢ. ﺑـﺮاي ﻓﺮاﯾﻨـﺪ رﻓﻊ ﻧﻮﯾﺰ ﻧﯿﺰ ﺳﻪ ﺷﺒﮑﻪ ي MCNN ﻣﺴﺘﻘﻞ ﺑﺮاي ﻫﺮ ﯾﮏ از ﺳﻪ روﯾﮑﺮد اﺳﺘﺨﺮاج اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ ﮐﻪ ارﺗﻘﺎع ﯾﺎﻓﺘﻪ از ﺷـﺒﮑﻪ ي Unet ﻣﯽﺑﺎﺷﺪ.

Todays, barcodes play a significant role in various industries, and among the two-dimensional barcodes, the most famous one is QR code (Quick Response code) that has grown widely. The main purpose of this paper is to provide a noise-cancellation method based on a autoencoder deep neural network that can be used to restore distorted and illegible QRs to readability. To create noise and distortion, unlike other articles that used added simulated noise to the image, the challenge of extracting QR coded into a color image was used to collect more realistic data by collecting real-world dataset. therefore we Have more reliable estimation of proposed QRs noise-canceling method. As a result, we created a comprehensive data set of distorted QRs from three different watermark extraction approaches after the screen-camera attack. For the noise reduction process, three independent MCNN networks ( which is an upgrade from the U-net network) are used for each of the three extraction approaches,