A computer-implemented method for determining a degree of homogeneity in one or more inspection images of cargo in one or more containers, comprising: determining (S12) whether a zone of interest in one or more processed inspection images comprises one or more patterns, each pattern defining a recognizable shape, intensity or texture having a macroscopic visual property, wherein the one or more processed inspection images are processed from one or more inspection images generated by an inspection system configured to inspect the one or more containers; and in the event that a plurality of patterns is determined (S12): extracting (S13) at least two regions in the zone of interest based on the determined plurality of patterns, determining (S14) whether the extracted at least two regions comprises at least two identical regions, in the event that no identical regions is determined (S14), classifying (S15) the one or more inspection images as having a degree of homogeneity below a predetermined inhomogeneity threshold, in the event that at least two identical regions is determined (S14), determining (S2) whether there is a variation V in the determined plurality of patterns and, if a variation in the determined plurality of patterns is identified (S2), classifying (S31) the one or more inspection images as having an intermediate degree of homogeneity comprised above the predetermined inhomogeneity threshold and below a predetermined homogeneity threshold. determining (S12) whether a zone of interest in one or more processed inspection images comprises one or more patterns, each pattern defining a recognizable shape, intensity or texture having a macroscopic visual property, wherein the one or more processed inspection images are processed from one or more inspection images generated by an inspection system configured to inspect the one or more containers; and in the event that a plurality of patterns is determined (S12): extracting (S13) at least two regions in the zone of interest based on the determined plurality of patterns, determining (S14) whether the extracted at least two regions comprises at least two identical regions, in the event that no identical regions is determined (S14), classifying (S15) the one or more inspection images as having a degree of homogeneity below a predetermined inhomogeneity threshold, in the event that at least two identical regions is determined (S14), determining (S2) whether there is a variation V in the determined plurality of patterns and, if a variation in the determined plurality of patterns is identified (S2), classifying (S31) the one or more inspection images as having an intermediate degree of homogeneity comprised above the predetermined inhomogeneity threshold and below a predetermined homogeneity threshold. extracting (S13) at least two regions in the zone of interest based on the determined plurality of patterns, determining (S14) whether the extracted at least two regions comprises at least two identical regions, in the event that no identical regions is determined (S14), classifying (S15) the one or more inspection images as having a degree of homogeneity below a predetermined inhomogeneity threshold, in the event that at least two identical regions is determined (S14), determining (S2) whether there is a variation V in the determined plurality of patterns and, if a variation in the determined plurality of patterns is identified (S2), classifying (S31) the one or more inspection images as having an intermediate degree of homogeneity comprised above the predetermined inhomogeneity threshold and below a predetermined homogeneity threshold. <EOS>