For over 3 decades, computer graphics technology has been developed to simulate physically accurate image of real scene. Meanwhile, useful tone mapping methods have been developed to map luminance range of the simulated image into that of usual monitor without perceptual distortion. However, it is difficult to reproduce accurate glossiness of real objects within the limited monitor luminance range. This also causes inaccurate glossiness sequence among several reproduced images. In this paper, relative-glossiness matching technique is proposed for reliable business to business (B to B) e-commerce system on 3D prints such as beverage cans, PET bottles, snack packages, and so on. The relative-glossiness-matching technique is introduced to preserve perceptual ratio of glossiness of the real 3D print objects in reproduced images. We also propose two operations to control surface-texture gloss and contrast gloss of reproduced images in Hunter's classification for physical gloss; adding Gaussian noise to surface normal in rendering process and scaling specular reflection in tone mapping. Procedure of subjective evaluation to determine the standard deviation of Gaussian noise and scaling factor for specular reflection is described. An experiment for the relative-glossiness matched images is performed using four types of real papers shaped into 3D cylinders. It was visually confirmed that the reproduced images preserved the glossiness sequence of the real 3D cylinder.