Relief reconstruction of rough-textured surface through image analysis

Abstract

In this study, we propose an original method for a 3D reconstruction of the relief of a textured rough surfaces. This 3D reconstruction is obtained through the elaboration of a photometric model, which takes into account camera and light source positions according to the plan of the rough surface. The proposed model expresses the gray level on the image according to the local relief variations. Three images of the same relief obtained under different angles of lighting are used to reconstruct the altitude map of the rough surface. The effectiveness of this method was checked by comparing the extracted relief to its corresponding relief obtained from a mechanical device method using autofocus laser sensor. This photometric model display good results in simulation experience and will be applied on real photographic images of road covering surface in order to study its wear level and its adherence.

Specularity and shadow detection for the multisource photometric reconstruction of a textured surface

“…This method is called photometric stereo and was largely studied these last decades [7][8][9]. For very short acquisition times and large Lambertian surfaces, the results of 3D surface analysis therefore approach the accuracy of laser methods [10,11]. At least three images without shadowing and representing a Lambertian surface, corresponding to three different lighting directions, are needed to apply photometric stereo.…”

Photometric reconstruction of a dynamic textured surface from just one color image acquisition

“…This method is called photometric stereo and was largely studied these last decades [7][8][9]. For very short acquisition times and large surfaces, the results of three-dimensional surface analysis then approach the accuracy of the laser methods [10,11]. However, relative motion between the camera and the object poses a problem for photometric stereo derived from a sequence of images in a dynamic environment.…”