Abstract: A method for correcting a geometrically distorted QR code includes oversampling modules of the QR code by dividing each module to F*F sample elements for forming an oversampling matrix, determining intensity for each sample element in the oversampling matrix, calculating an average intensity of the oversampling matrix, subtracting the average intensity from intensity of each sample element in the oversampling matrix, filtering intensity values for determining an average value for each sample element, tracking a sample element corresponding a center of each module and determining color of each module based on intensities of sample elements corresponding the center of each module by using recursion. The disclosure further relates to a computer program product and device performing the method.
Abstract: A method for correcting a geometrically distorted QR code include oversampling modules of the QR code by dividing each module to F*F sample elements for forming an oversampling matrix, determining intensity for each sample element in the oversampling matrix, calculating an average intensity of the oversampling matrix, subtracting the average intensity from intensity of each sample element in the oversampling matrix, filtering intensity values for determining an average value for each sample element, tracking a sample element corresponding a center of each module and determining color of each module based on intensities of sample elements corresponding the center of each module by using recursion. The disclosure further relates to a computer program product and device performing the method.
Abstract: a method includes capturing image data by at least one camera of a camera system, analysing the image data, detecting a machine readable code including configuration data from the image data, and configuring the camera system on the basis of the configuration data of the machine readable code. The method further relates to a camera system performing the method and to a computer program product.