The Quick Response (QR) code when contrasted with standard QR(standardized identifications) has quick comprehensibility and more prominent cache limit. QR code can be perused by any imaging gadgets, for example, camera, scanner and so on. Data can be retrieved from vertical and even segments. In this paper, we propose another level i.e. Private level to the QR code alongside standard level known as Public level. Private level is built by utilizing ECDSA (Elliptic Curve Digital Signature Algorithm) to improve the higher security of code. Dark modules of QR code are substituted with textured patterns so code becomes responsive to Print-and Scan. QR code having two levels will serve as an authentication process for any report. A textured pattern likewise helps in separating copy and unique duplicate of report consequently supporting authentication. As the extent of code expands it turns out to be more hard to invade into code or translate it. The limit furthest reaches of the QR code can be fundamentally improved by extending the code letters(The codewords are squares of images that are encoded utilizing a larger number of images than the first incentive to be sent).
Machine learning algorithms
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL