Method for contactless and non-destructive verification of the validity of a component that has a production-related technical surface texture using a laser light-induced speckle pattern analysis, characterized in that at least one area of a surface of the component containing the surface texture is exposed to laser light, forming a planar speckle pattern that is influenced by the surface texture, which pattern is detected with spatial resolution and converted into a 2-dimensional, digital speckle pattern signal data record, SMS for short, which is subjected to at least one image signal processing routine, in which at least one parameter that is assignable to the SMS is determined, and is compared in each case with a target parameter to determine a deviation, which is used as a basis for a comparison criterion that is used for the validity verification, wherein the image signal processing routine creates a) a grey value transition matrix, b) a histogram, and/or c) an image intensity statistics for the SMS and - in case a) a contrast value C = Σ m,n (m - n) 2 G mn and/or a homogeneity H = ∑ m , n 1 1 + m − n 2 G mn is determined as the parameter, wherein m , n : row and column number of the grey value transition matrix, G mn : value in the grey value transition matrix, - in case b) an entropy value E = − ∑ I = 0 255 rel I ∗ log 2 rel I is determined as the parameter, wherein rel ( I ) normalised histogram numbers of a given grey value I , which is defined as an integer in the range from 0 to 255, and - in case c) a deviation D = ∑ x ∑ y I xy − M 2 N − 1 is determined as the parameter, wherein M = ∑ x ∑ y I xy N : average grey value of all signal data within the SMS, I xy : grey value of signal data (x, y) in the SMS and N : total number of the signal data in the SMS. - in case a) a contrast value C = Σ m,n (m - n) 2 G mn and/or a homogeneity H = ∑ m , n 1 1 + m − n 2 G mn is determined as the parameter, wherein m , n : row and column number of the grey value transition matrix, G mn : value in the grey value transition matrix, contrast value C = Σ m,n (m - n) 2 G mn and/or a homogeneity H = ∑ m , n 1 1 + m − n 2 G mn is determined as the parameter, wherein m , n : row and column number of the grey value transition matrix, G mn : value in the grey value transition matrix, transition matrix, G mn : value in the grey value transition matrix, - in case b) an entropy value E = − ∑ I = 0 255 rel I ∗ log 2 rel I is determined as the parameter, wherein rel ( I ) normalised histogram numbers of a given grey value I , which is defined as an integer in the range from 0 to 255, and entropy value E = − ∑ I = 0 255 rel I ∗ log 2 rel I is determined as the parameter, wherein rel ( I ) normalised histogram numbers of a given grey value I , which is defined as an integer in the range from 0 to 255, and grey value I , which is defined as an integer in the range from 0 to 255, and - in case c) a deviation D = ∑ x ∑ y I xy − M 2 N − 1 is determined as the parameter, wherein M = ∑ x ∑ y I xy N : average grey value of all signal data within the SMS, I xy : grey value of signal data (x, y) in the SMS and N : total number of the signal data in the SMS. deviation D = ∑ x ∑ y I xy − M 2 N − 1 is determined as the parameter, wherein M = ∑ x ∑ y I xy N : average grey value of all signal data within the SMS, I xy : grey value of signal data (x, y) in the SMS and N : total number of the signal data in the SMS. data within the SMS, I xy : grey value of signal data (x, y) in the SMS and N : total number of the signal data in the SMS. <EOS>