Quick Response code Scanner

Computer vision

Advances in semiconductor manufacturing processes and large scale integration keep pushing demanding applications further away from centralized processing, and closer to the edges of the network (i.e. Edge Computing). It has become possible to perform complex in-network image processing using low-power embedded smart cameras, enabling a multitude of new collaborative image processing applications. This paper introduces the concept of QR code scanning using Open MV, a new low-power smart camera that lends itself naturally to wireless sensor networks and machine vision applications. The uniqueness of this platform lies in running an embedded Python 3 interpreter, allowing its peripherals and machine vision library to be scripted in Python. In addition, its hardware is extensible via modules that augment the platform with new capabilities.This research work concentrate on the concept of QR code and the scanner used to detect the QR code successfully . A QR code (short for "quick response" code) is a type of barcode that contains a matrix of dots. QR code holds data like simple text , addresses , phone numbers ,email addresses , URL , price of commodities etc . It can be scanned using a QR code scanner or a smart phone with built-in camera. For example, scanning a QR code with your phone might open a URL in your phone's web browser . Firstly , the obvious drawback of smart phones is that it requires internet connection to read the QR codes . QR codes cannot be scanned if there is no internet connection. Secondly , the smart phones are far more expensive. Thirdly, the speed of scanning QR code is less in smart phones for industry. This paper proposes a solution to many of above problems by using Open MV Cam M7 smart vision camera. By using the Open MV cam M7 the rate of scanning is increased thereby reducing the expenses.

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