Abstract: A method and system for evaluating crack intensity on polymeric sheet based on predetermined scale of crack intensity grades, which includes the steps of a) recording digital image of at least portion of surface of polymeric sheet using apparatus for recording digital images; and b) automatic classification of crack intensity by computer-implemented program for pattern recognition by means of trained artificial neural network, including 1) inputting digital image or one or more subareas of digital image to trained artificial neural network as input data, 2) classification by artificial neural network by assigning grade from predetermined scale of crack intensity grades to digital image or one or more subareas and 3) outputting assigned grade or grades for digital image and/or one or more subareas as output data, wherein artificial neural network is trained in advance in learning phase with plurality of digital images or subareas thereof of polymeric sheet surface portions.

Abstract: A method and system for evaluating crack intensity on polymeric sheet based on predetermined scale of crack intensity grades, which includes the steps of a) recording digital image of at least portion of surface of polymeric sheet using apparatus for recording digital images; and b) automatic classification of crack intensity by computer-implemented program for pattern recognition by means of trained artificial neural network, including 1) inputting digital image or one or more subareas of digital image to trained artificial neural network as input data, 2) classification by artificial neural network by assigning grade from predetermined scale of crack intensity grades to digital image or one or more subareas and 3) outputting assigned grade or grades for digital image and/or one or more subareas as output data, wherein artificial neural network is trained in advance in learning phase with plurality of digital images or subareas thereof of polymeric sheet surface portions.