This work investigates the use of Reflectance Transformation Imaging (RTI) rendering for visual inspection. This imaging technique is being used more and more often for the inspection of the visual quality of manufactured surfaces. It allows reconstructing a dynamic virtual rendering of a surface from the acquisition of a sequence of images where only the illumination direction varies. We investigate, through psychometric experimentation, the influence of different essential parameters in the RTI approach, including modeling methods, the number of lighting positions and the measurement scale. In addition, to include the dynamic aspect of perception mechanisms in the methodology, the psychometric experiments are based on a design of experiments approach and conducted on reconstructed visual rendering videos. The proposed methodology is applied to different industrial surfaces. The results show that the RTI approach can be a relevant tool for computer-aided visual inspection. The proposed methodology makes it possible to objectively quantify the influence of RTI acquisition and processing factors on the perception of visual properties, and the results obtained show that their impact in terms of visual perception can be significant.
Reflectance Transformation Imaging (RTI) is a technique for estimating the surface local angular reflectance and characterizing the visual properties by varying lighting directions and capturing a set of stereo-photometric images. The proposed method, namely HD-RTI, is based on the coupling of RTI and HDR imaging techniques. The HD-RTI automatically optimizes the necessary exposure times for each angle of illumination by using the response of the scene. Our method is applied to industrial surfaces with micro-scratches from which we will estimate saliency information. Results show that coupling HDR and RTI enhance the characterization and therefore the discrimination on the surfaces visual saliency maps. It leads to an increase in robustness for visual quality assessment tasks.
Reflectance Transformation Imaging (RTI) is a non-contact technique which consists in acquiring a set of multi-light images by varying the direction of the illumination source on a scene or a surface. This technique provides access to a wide variety of local surface attributes which describe the angular reflectance of surfaces as well as their local microgeometry (stereo photometric approach). In the context of the inspection of the visual quality of surfaces, an essential issue is to be able to estimate the local visual saliency of the inspected surfaces from the often-voluminous acquired RTI data in order to quantitatively evaluate the local appearance properties of a surface. In this work, a multi-scale and multi-level methodology is proposed and the approach is extended to allow for the global comparison of different surface roughnesses in terms of their visual properties. The methodology is applied on different industrial surfaces, and the results show that the visual saliency maps thus obtained allow an objective quantitative evaluation of the local and global visual properties on the inspected surfaces.
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