QR Code Augmented Reality tracking with merging on conventional marker based Backpropagation neural network

QR Code Augmented Reality (QRAR) is an Augmented Reality does not require preregistration, it has 10
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combination ID-encoded and can be used on the public AR application. The results from previous research are 6 DOF tracking method less accurate, require small computation power and unstable marker. We propose merging conventional marker with QR Code, but it will have noise on the QR Code Finder Patter (QRFP) under perspective distortion, so we propose a Backpropagation method to keep detecting the QRFP and the method preceded by feature extraction with low level image processing. The methods we have proposed, achieve accurate 6 DOF, runs at 35.41 fps and stable marker as conventional marker.