Abstract

An optical–digital approach to the problem of automatic detection of dents and scratches on specular or semispecular surfaces is presented. The method uses the optical reflecting properties of dents and scratches to locate and detect them. Dents are found by a grid projection and encoding technique; scratches are found by using the property that diffuse reflectors scatter over a wider angle (Lambert’s law) than specular ones and, therefore, seem brighter when viewed at certain angles. The procedure for finding dents and scratches was found to be very robust: dents as small as 1% of the viewed field and 0.0053 cm (0.0021 in.) deep and scratches as small as 0.003 cm (0.001 in.) wide and 0.00064 cm (0.00025 in.) deep and of variable minimum length were easily detected using nonspecially prepared samples.

© 1982 Optical Society of America

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References

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  1. G. N. Saridis, D. M. Brandin, Automatika 15, 505 (1979).
    [CrossRef]
  2. J. L. Mundy, G. B. Porter, “Visual Inspection of Metal Surfaces,” in Proceedings, Fifth International Conference on Pattern Recognition (IEEE Cat. No. 80 CH 1499-3, Miami, FL, 1980).
  3. G. B. Porter, J. L. Mundy, Computer 13, 40 (1980).
    [CrossRef]
  4. B. G. Batchelor, G. A. Williams, in “Imaging Appliations for Automated Inspection and Assembly,” Proc. Soc. Photo-Opt. Instrum. Eng. 132, (1979).
  5. P. M. Will, K. S. Pennington, “Grid Coding: A Microprocessing Technique for Robot and Machine Vision,” in Proceedings, Second International Conference on Artificial Intelligence (British Computer Soc., London, 1971).
  6. M. Potmesil, H. Freeman, “Computer Descriptions of Curved-Surface Objects,” Tech. Report CRL-58, Rensselaer Polytechnic Institute, Troy, N.Y. (June, 1978).
  7. H. W. Lippincott, “Automatic Detection of Dent and Scratch Defects on Flat, Specular Surfaces,” M.S. Thesis, Rensselaer Polytechnic Institute, Troy, New York (Aug.1981).
  8. A. Rosenfeld, A. C. Kak, Digital Picture Processing (Academic, New York, 1976).
    [CrossRef]

1980 (1)

G. B. Porter, J. L. Mundy, Computer 13, 40 (1980).
[CrossRef]

1979 (2)

B. G. Batchelor, G. A. Williams, in “Imaging Appliations for Automated Inspection and Assembly,” Proc. Soc. Photo-Opt. Instrum. Eng. 132, (1979).

G. N. Saridis, D. M. Brandin, Automatika 15, 505 (1979).
[CrossRef]

Batchelor, B. G.

B. G. Batchelor, G. A. Williams, in “Imaging Appliations for Automated Inspection and Assembly,” Proc. Soc. Photo-Opt. Instrum. Eng. 132, (1979).

Brandin, D. M.

G. N. Saridis, D. M. Brandin, Automatika 15, 505 (1979).
[CrossRef]

Freeman, H.

M. Potmesil, H. Freeman, “Computer Descriptions of Curved-Surface Objects,” Tech. Report CRL-58, Rensselaer Polytechnic Institute, Troy, N.Y. (June, 1978).

Kak, A. C.

A. Rosenfeld, A. C. Kak, Digital Picture Processing (Academic, New York, 1976).
[CrossRef]

Lippincott, H. W.

H. W. Lippincott, “Automatic Detection of Dent and Scratch Defects on Flat, Specular Surfaces,” M.S. Thesis, Rensselaer Polytechnic Institute, Troy, New York (Aug.1981).

Mundy, J. L.

G. B. Porter, J. L. Mundy, Computer 13, 40 (1980).
[CrossRef]

J. L. Mundy, G. B. Porter, “Visual Inspection of Metal Surfaces,” in Proceedings, Fifth International Conference on Pattern Recognition (IEEE Cat. No. 80 CH 1499-3, Miami, FL, 1980).

Pennington, K. S.

P. M. Will, K. S. Pennington, “Grid Coding: A Microprocessing Technique for Robot and Machine Vision,” in Proceedings, Second International Conference on Artificial Intelligence (British Computer Soc., London, 1971).

Porter, G. B.

G. B. Porter, J. L. Mundy, Computer 13, 40 (1980).
[CrossRef]

J. L. Mundy, G. B. Porter, “Visual Inspection of Metal Surfaces,” in Proceedings, Fifth International Conference on Pattern Recognition (IEEE Cat. No. 80 CH 1499-3, Miami, FL, 1980).

Potmesil, M.

M. Potmesil, H. Freeman, “Computer Descriptions of Curved-Surface Objects,” Tech. Report CRL-58, Rensselaer Polytechnic Institute, Troy, N.Y. (June, 1978).

Rosenfeld, A.

A. Rosenfeld, A. C. Kak, Digital Picture Processing (Academic, New York, 1976).
[CrossRef]

Saridis, G. N.

G. N. Saridis, D. M. Brandin, Automatika 15, 505 (1979).
[CrossRef]

Will, P. M.

P. M. Will, K. S. Pennington, “Grid Coding: A Microprocessing Technique for Robot and Machine Vision,” in Proceedings, Second International Conference on Artificial Intelligence (British Computer Soc., London, 1971).

Williams, G. A.

B. G. Batchelor, G. A. Williams, in “Imaging Appliations for Automated Inspection and Assembly,” Proc. Soc. Photo-Opt. Instrum. Eng. 132, (1979).

Automatika (1)

G. N. Saridis, D. M. Brandin, Automatika 15, 505 (1979).
[CrossRef]

Computer (1)

G. B. Porter, J. L. Mundy, Computer 13, 40 (1980).
[CrossRef]

Proc. Soc. Photo-Opt. Instrum. Eng. (1)

B. G. Batchelor, G. A. Williams, in “Imaging Appliations for Automated Inspection and Assembly,” Proc. Soc. Photo-Opt. Instrum. Eng. 132, (1979).

Other (5)

P. M. Will, K. S. Pennington, “Grid Coding: A Microprocessing Technique for Robot and Machine Vision,” in Proceedings, Second International Conference on Artificial Intelligence (British Computer Soc., London, 1971).

M. Potmesil, H. Freeman, “Computer Descriptions of Curved-Surface Objects,” Tech. Report CRL-58, Rensselaer Polytechnic Institute, Troy, N.Y. (June, 1978).

H. W. Lippincott, “Automatic Detection of Dent and Scratch Defects on Flat, Specular Surfaces,” M.S. Thesis, Rensselaer Polytechnic Institute, Troy, New York (Aug.1981).

A. Rosenfeld, A. C. Kak, Digital Picture Processing (Academic, New York, 1976).
[CrossRef]

J. L. Mundy, G. B. Porter, “Visual Inspection of Metal Surfaces,” in Proceedings, Fifth International Conference on Pattern Recognition (IEEE Cat. No. 80 CH 1499-3, Miami, FL, 1980).

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Figures (12)

Fig. 1
Fig. 1

Configuration of dent detection system: a uniformly illuminated square grid mask is reflected by the test sample into the imaging system of a TV camera.

Fig. 2
Fig. 2

Test sample with both indents and outdents.

Fig. 3
Fig. 3

Video image of the characteristic grid coding for indent flaws.

Fig. 4
Fig. 4

Video image of the characteristic grid coding for outdent flaws.

Fig. 5
Fig. 5

Video image of an indent flawed sample.

Fig. 6
Fig. 6

Visual display of the output of the program showing the location of the dent and its approximate size (three grid units).

Fig. 7
Fig. 7

Talysurf 4 profile, of a typical scratch on flat metal surfaces.

Fig. 8
Fig. 8

Diagram of experimental configuration for scratch detection system.

Fig. 9
Fig. 9

Test sample showing an 8.9-cm long scratch being illuminated by the SDTS and viewed by the TV camera.

Fig. 10
Fig. 10

Video image of the sample in Fig. 9.

Fig. 11
Fig. 11

Gray-scale histogram of the sample displayed on the graphic overlay of the EyeCom system.

Fig. 12
Fig. 12

Detected and tracked scratches found by the SDTS algorithm. The reconstructed scratches detected are shown using TL = 6, TH = 9.

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