An Intelligent QR Code Scanning System for Visually-Impaired Users

While QR code reading finds its applications in many diverse fields like retail environments, industries, product identification, marketing, education, warcraft etc., this work aims to streamline the performance of the algorithm according to the requirements of a visually-impaired user for assistance in product identification and or way-finding in both indoor and outdoor environments. Vision is a gift and being able to make up for it for someone would be a great cause to serve. Given the laborious hassle involved taking their route and the alarming consequence of taking the stairs instead of an elevator, this work aims to contribute a robust and effective QR code scanning system addressing the possible problems and challenges associated with reading the QR code within such an environment using a deep learning based methodology. Especially in case of an emergency to identify a fire exit for instance, this work will effectively contribute towards robust recognition of the QR Code even when it might be in a condition not interpretable by standard QR Code readers. It was concluded that while the same Computer Vision algorithm can be tweaked to execute targeted drone attacks, it is also the same technology that can assist humanity hand in hand and help visually-impaired users in seeing the missed and fulfill the purpose that technology was originally created for i.e. to serve humanity, rather than the opposite.