Quick Response Code Recovery using Sparse Signal Processing Approach

The quick response code has been used in many applications nowadays. In this work, we examined the encoding performance when code image is highly under-sampled. The random under-sampling process is considered and motivated by the Compressive Sensing scenario. The achieved results prove that the code encoding can be successfully done after reconstruction even when 70% of the pixels are missing.