Efficient 3D characterization of raised topological defects in smooth specular coatings

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Abstract

Many smooth, highly specular coatings, such as automotive paints and appliance coatings, are subjected to considerable performance demands and manufacturers spend significant sums each year to monitor and repair coating surface quality. Additionally, changing product specifications and environmental regulations will continue to affect the processing parameters that influence surface appearance and quality. Therefore, it is vital to develop robust methods to monitor surface quality on-line and continuously examine the processes that significantly affect surface appearance in real-time. As a critical step, this paper presents a cost-effective machine vision system design that utilizes surface reflectance models as a rational basis. Experimental and numerical investigations of diffuse angle images of specular coated surfaces confirm that these images yield a three-dimensional characterization of surface defects, efficiently, from a single image.

Section snippets

Introduction and motivation

Many smooth, specular coatings (e.g., automotive paints, appliance coatings, etc.) are subjected to considerable performance demands. Though the primary function of the coated finish is to enhance durability by protecting the product from corrosion, it is well established that surface appearance is a key factor in perceived product quality [1]. Additionally, the importance of the surface finish impacts significantly more than the initial buying process, as it is estimated that manufacturers

Related work and rational basis

This section contains a summary of related surface appearance research in Section 2.1; the rational basis for the work presented in this paper is discussed in the remaining sections. A review of the surface reflectance model for isotropic surfaces is presented in Section 2.2, followed by an overview of our proposed approach and our prior research results in Section 2.3. Section 2.4 describes the use of diffuse angle images to observe and characterize topological defects, based upon the surface

Characterization of defect information from diffuse images

Initially, based upon the rational basis and preliminary numerical and experimental findings presented in Section 2, images of a smooth, specular surface containing seed defects acquired at a sufficiently diffuse angle were expected yield high contrast images which quickly and effectively determined the number of seed defects and their locations (i.e., it was initially expected that a near one-to-one correlation would exist between the number of image highlights and the number of defects

Results

This paper focuses on the efficacy of single diffuse angle images to report accurate defect height information; both a numerical study (which implemented the indirect reflection discussed in Section 3.2.4) and experimental investigations were conducted to validate the hypothesis that a single diffuse image could yield efficient information on defect location and height for seed defects. In the initial experiment, captured images of single raised defects were illuminated with a variable

Summary

To facilitate real-time control of the coating process, a robust, efficient inspection technology to detect common surface defects is required. In the long-term goal described in the introduction, information from a machine vision system, such as the diffuse captured images presented here, is expected to serve as partial input to an intelligent, adaptive control scheme which compares actual surface quality to a desired standard, links complex processing conditions with surface quality to assess

Acknowledgments

This material is based upon work supported by the National Science Foundation, Division of Design, Manufacture and Industrial Innovation, under Grants DMI-9984867 and DMI-0074976, and Toyota Motor Manufacturing North America. The authors gratefully acknowledge undergraduate researcher James Casalino for his work in obtaining Eq. (7) and programming this equation on-board the DVT 530 to facilitate preliminary real-time studies.

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