Aging of infrastructures has been a worldwide issue, and cost saving by shifting to preventive maintenance is urgent. Especially, damage detection of concrete bridge decks is one of the most important subjects, because of the significant repair costs due to its complicated structure. Rebars are the fundamental components of bridge decks, and they often become the trigger of bridge decks’ damages. Previous researches have been focused on detecting the locations of rebars in cross section images acquired by single-channel ground penetrating radar (GPR), however, no research has reproduced 3D rebar mesh arrangement from radar volume images acquired by multi-channel GPR.This paper proposes a method that reproduces 3D rebar mesh that contains the data of vertex location and reflection time from radar volume images. Real scale bridge deck specimens were created in this study and reflections of electromagnetic waves were observed utilizing an on-vehicle GPR. In the proposed method, 3D filtering based on the 3D DFT theory for the noise reduction was applied. Also, automation in detection of the rebar depth was achieved focusing on edges of the images. As a result, 3D rebar meshes were successfully reproduced with appropriate distribution rebar spacing. Also, the method was applied to radar data acquired from a bridge in service. The proposed method effectively functioned for in-service bridge data, and automatically reproduced the mesh of 21m length.