Recognition of QR Codes Resistant to Affine Transformations

Recognizing Quick Response Codes in images poses challenges due to various factors. While Quick Response Codes are meticulously crafted for efficient recognition, existing libraries often necessitate a clear binary image of the Quick Response Code for successful decoding. This demands users to accurately align their cameras and maintain specific orientations relative to the Quick Response Code, introducing inconveniences and potential errors, particularly when ideal conditions cannot be met. In this study, we introduce techniques to enhance the precision of Quick Response Code detection through conventional image processing methods and provide quantitative assessments to gauge the efficacy of our proposed algorithm. Our approach presents a novel method for identifying Quick Response Codes in images, derived from a modified version of the Viola and Jones method. Furthermore, we outline the principal characteristics of the Quick Response Codes utilized in developing our detection method, alongside offering a succinct overview of the original Viola and Jones technique.