Bas-relief Modeling from RGB Monocular Images with Regional Division Characteristics
Authors: Wu Xinli , Luo Jiali , Zhang Minxiong , Yang Wenzhen 
Published: November 2021

Abstract
Bas-relief, a form of sculpture art representation, has the general characteristics of sculpture art and satisfies people’s visual and tactile feelings by fully leveraging the advantages of painting art in composition, subject matter, and spatial processing. Bas-relief modeling using images is generally classified into the method based on the three-dimensional (3D) model, that based on the image depth restoration, and that based on multi-images. The 3D model method requires the 3D model of the object in advance. Bas-relief modeling based on the image depth restoration method usually either uses a depth camera to obtain object depth information or restores the depth information of pixels through the image. Bas-relief modeling based on the multi-image requires a short running time and has high efficiency in processing high resolution level images. Our method can automatically obtain the pixel height of each area in the image and can adjust the concave–convex relationship of each image area to obtain a bas-relief model based on the RGB monocular image. First, the edge contour of an RGB monocular image is extracted and refined by the Gauss difference algorithm based on tangential flow. Subsequently, the complete image contour information is extracted and the region-based image segmentation is used to calibrate the region. This method has improved running speed and stability compared with the traditional algorithm. Second, the regions of the RGB monocular image are divided by the improved connected-component labeling algorithm. In the traditional region calibration algorithm, the contour search strategy and the inner and outer contour definition rules of the image considered result in a low region division efficiency. This study uses an improved contour-based calibration algorithm. Then, the 3D pixel point cloud of each region is calculated by the shape-from-shading algorithm. The concave–convex relationships among these regions can be adjusted by human–computer interaction to form a reasonable bas-relief model. Lastly, the bas-relief model is obtained through triangular reconstruction using the Delaunay triangulation algorithm. The final bas-relief modeling effect is displayed by OpenGL. In this study, six groups of images are selected for conducting regional division tests, and the results obtained by the proposed method and other existing methods are compared. The proposed algorithm shows improved image processing running time for different complexity levels compared with the traditional two-pass scanning method and seed filling method (by approximately 2 s) and with the contour tracking method (by approximately 4 s). Next, image depth recovery experiments are conducted on four sets of images, namely the “ treasure seal,” “Wen Emperor seal,” “lily pattern,” and “peacock pattern,” and the results are compared. The depth of the image obtained by the traditional algorithm is generally lower than the actual plane, and the relative height of each region is not consistent with the actual situation. The proposed algorithm provides height values consistent with the height value information judged in the original image and adjusts the accurate concave–convex relationships. Moreover, the noise in the image is reduced and relatively smooth surfaces are obtained, with accurate concave–convex relationships. The proposed bas-relief model based on RGB monocular images can automatically determine the pixel height of each image area in the image and adjust the concave–convex relationship of each image area. In addition, it can recover the 3D model of the object from the image, enrich the object of bas-relief modeling, and expand the creation space of bas-relief, thereby improving the production efficiency of the bas-relief model based on RGB monocular images. The method has certain shortcomings, which require further exploration. For example, during the process of image contour extraction for region division, small differences exist between the obtained result and the actual situation, which can in turn affect the image depth recovery in the later stage. In addition, partial distortion may occur in the process of 3D reconstruction, which requires further research on point cloud data processing to reconstruct a high-quality three-dimensional surface.