The analysis of surface texture using photometric stereo acquisition and gradient space domain mapping

Abstract A novel machine vision based inspection technique was developed for the analysis of three-dimensional (3D) surface textural patterns. Previous machine vision based methods of texture analysis have in general analysed projected two-dimensional (2D) textural patterns. This paper presents an innovative approach for the direct analysis of 3D texture topography. The method employed has particular application for the evaluation of textures frequently encountered during numerous manufacturing and finishing processes. A 3D surface topographic description is acquired using a photometric stereo technique. A method of gradient space domain mapping and surface reconstruction are used to characterise textural form, shape and regularity, and to quantify any observed deviation in an idealised form in relation to a CAD based prototypical texture model. Unlike conventional viewer centred methods for the assessment of projected texture, the technique offers a 3D object centred analysis, uses a fixed lighting configuration, is largely insensitive to a variation in object pose, and is rapid in operation. These aspects are of considerable advantage in terms of practical application. The technique was applied to real texture samples, and a selection of experimental results are presented in this paper.

[1]  G A H Al-Kindi,et al.  An application of machine vision in the automated inspection of engineering surfaces , 1992 .

[2]  Melvyn L. Smith,et al.  Surface texture analysis based upon the visually acquired perturbation of surface normals , 1997, Image Vis. Comput..

[3]  Melvyn L. Smith,et al.  Gradient space analysis of surface defects using a photometric stereo derived bump map , 1999, Image Vis. Comput..

[4]  E. North Coleman,et al.  Obtaining 3-dimensional shape of textured and specular surfaces using four-source photometry , 1982, Comput. Graph. Image Process..

[5]  D. K. Sharma,et al.  Machined surface texture parameters for occluded scene segmentation , 1994, Electronic Imaging.

[6]  Shivakumar Raman,et al.  Texture analysis using computer vision , 1991 .

[7]  Eam Khwang Teoh,et al.  Computer based wafer inspection system , 1991, Proceedings IECON '91: 1991 International Conference on Industrial Electronics, Control and Instrumentation.

[8]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

[9]  Robert J. Woodham,et al.  Reflectance map techniques for analyzing surface defects in metal castings , 1978 .

[10]  P. Mengel.  Automated inspection of solder joints on PC boards by supplementary processing of 3D and gray-level images , 1990, [Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society.

[11]  Harry Wechsler,et al.  Texture analysis — a survey , 1980 .

[12]  Berthold K. P. Horn.  Sequins and Quills - Representations for Surface Topography. , 1979 .

[13]  Jürgen Beyerer,et al.  Model-based analysis of groove textures with applications to automated inspection of machined surfaces , 1995 .

[14]  Jonas Gårding,et al.  Direct Estimation of Shape from Texture , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Berthold K. P. Horn.  Fan-beam reconstruction methods , 1979, Proceedings of the IEEE.

[16]  Josef Kittler,et al.  Texture defect detection: a review , 1992, Defense, Security, and Sensing.

[17]  James F. Blinn,et al.  Simulation of wrinkled surfaces , 1978, SIGGRAPH.

[18]  Alex Pentland,et al.  Local Shading Analysis , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Sven Utcke,et al.  Advanced Quality Inspection through Physics-Based Vision , 1995 .

[20]  Mubarak Shah,et al.  Integration of shape from shading and stereo , 1995, Pattern Recognit..

[21]  R. Haataja,et al.  Expert Systems for the Automatic Surface Inspection of Steel Strip , 1992 .

[22]  Berthold K. P. Horn,et al.  Determining Shape and Reflectance Using Multiple Images , 1978 .

[23]  G. Awcock,et al.  Applied Image Processing , 1995 .

[24]  A. R. Rao,et al.  A CLASSIFICATION SCHEME FOR VISUAL DEFECTS ARISING IN SEMICONDUCTOR WAFER INSPECTION , 1990 .

[25]  Byungil Kim,et al.  Depth and shape from shading using the photometric stereo method , 1991, CVGIP Image Underst..