The q-rung picture fuzzy hypersoft set (q-RPFHSS) is a generalization of the picture fuzzy hypersoft set and has tremendous potential for dealing with unreliable circumstances with no restrictions. The measure of similarity between two structures is necessary in some situations where the sum of the values of membership, non-membership, and neutral membership is greater than one. In this study, we proposed a new distance measure of q-rung picture fuzzy hypersoft set to find the discrimination between two objects. The fundamental axioms of the measures have been emphasized, and their properties have been studied. Next, similarity measures are defined based on distance measures for q-RPFHSS which are capable of distinguishing highly similar elements. Further, some theorems that express the properties of measures are proved. To check the accuracy of defined measures we give an illustration section. Further, a pattern recognition algorithm based on q-RPFHSS is introduced by using the proposed similarity measures to classify the objects.