Abstract: A computer implemented method for detecting and reading a barcode in an image of a marked glass substrate, the method taking as input a raster image of at least one portion of the marked glass substrate and providing as output an abstract image of the barcode, the method including (a) computing a probability occurrence ? of the barcode in the raster image with a first trained convolutional artificial neural network; (b) computing coordinates of representative points of a boundary of the barcode in the raster image-according to a given threshold ? for the probability occurrence ? computed at (a); (c) cropping the raster image to the boundary of the barcode according to the coordinates computed at (b), and (d) computing with a second trained convolutional artificial neural network a tensor of probabilities for each pixel of the cropped raster image, the tensor being the abstract image of the barcode.

Abstract: A computer implemented method for detecting and reading a barcode in an image of a marked glass substrate, the method taking as input a raster image of at least one portion of the marked glass substrate and providing as output an abstract image of the barcode, the method including (a) computing a probability occurrence ? of the barcode in the raster image with a first trained convolutional artificial neural network; (b) computing coordinates of representative points of a boundary of the barcode in the raster image-according to a given threshold ? for the probability occurrence ? computed at (a); (c) cropping the raster image to the boundary of the barcode according to the coordinates computed at (b), and (d) computing with a second trained convolutional artificial neural network a tensor of probabilities for each pixel of the cropped raster image, the tensor being the abstract image of the barcode.