Abstract
This paper deals with the inspection of highly reflective chrome-coated rings used in textile machinery using machine vision. These rings are mass produced in very large numbers, and the inspection was done manually using an optical microscope. Introduction of vision inspection using algorithms supplied by a commercial vendor had not helped the industry to achieve 100% quality inspection. In order to improve inspection speed and to ensure 100% quality inspection, it was absolutely essential to improve the complete inspection process, and it was also required to classify defective and non-defective components by a proper sorting algorithm. The effect of the curved, reflective nature of material and the real-time inspection make the imaging and defect detection and classification difficult. In the present study, four different algorithms based on Fourier filtering, auto-median, image convolution, and single-step thresholding approaches were used for defect detection, and then their performances were compared with reference to efficiency of defect classification and speed. The complete procedure, analysis, and the results of different image processing algorithms used in defect detection are reported in this paper.
Similar content being viewed by others
References
Tsai DM, Kuo CC (2007) Defect detection in inhomogenously textured sputtered surfaces using 3D Fourier image reconstruction. Mach Vis Appl 18:383–400. doi:10.1016/S0262-8856(99)00009-8
Zhang X, Krewet C, Kuhlenkötter B (2006) Automatic classification of defects on the product surface in grinding and polishing. Int J Mach Tools Manuf 46:59–69. doi:10.1016/j.ijmachtools.2005.03.013
Wiltschi K, Pinz A, Lindberg T (2000) An automatic scheme for steel quality inspection. Mach Vis Appl 12:113–128. doi:10.1007/s001380050130
Rosati G, Boschetti G, Biondi A, Rossi A (2009) Real-time defect detection on highly reflective curved surfaces. Opt Lasers Eng 47(3–4):379–384. doi:10.1016/j.optlaseng.2008.03.010
Sun Y, Bai P, Sun HY, Zhou P (2005) Real time automatic defect detection of weld defects in steel pipe. NDT E Int 38:522–528. doi:10.1016/j.ndteint.2005.01.011
Luo PF, Liou SS (1998) Measurement of curved surfaces by stereo vision and error analysis. Opt Lasers Eng 30:471–486. doi:10.1016/S0143-8166(98)00052-9
Abramovich G, Barhak J, Spicer P (2005) Reconfigurable array for machine vision inspection (RAMVI) Proceedings of the 3rd International CIRP Conference on Reconfigurable Manufacturing. Ann Arbor, USA, R-01, May 10–12, 2005
Samak D, Fischer A, Rittel D (2007) 3D reconstruction and visualization of microstructure surfaces from 2D images. Ann CIRP 56(1):149–152. doi:10.1016/j.cirp.2007.05.036
Porteus JO, Spiker CJ, Franck JB (1986) Correlation between He–Ne scatter and 2.7 μm pulsed laser damage at coating defects. Appl Opt 25(21):3871–3879. doi:10.1364/AO.25.003871
Marrs CD, Porteus JO (1985) Nondestructive defect detection in laser optical coatings. J Appl Phys 57(5):1719–1722. doi:10.1063/1.334443
Khalili K, Webb P (2007) The development and application of a multiple wavelength illumination technique for the vision-based process monitoring of aero-structure riveting. Mach Vis Appl 18:73–83. doi:10.1007/s00138-006-0049-8
Lee MFR, deSilva CW, Croft EA, Wu QMJ (2000) Machine vision system for curved surface inspection. Mach Vis Appl 12:177–188. doi:10.1007/s001380000043
Aluze D, Merienne F, Dumont C, Gorria P (2002) Vision system for defect imaging, detection, and characterization on a specular surface of a 3D object. Image Vis Comput 20:569–580. doi:10.1016/S0262-8856(02)00046-X
Pfeifer T, Wiegers L (1998) Adaptive control for the optimized adjustment of imaging parameters for surface inspection using machine vision. Ann CIRP 47(1):459–462. doi:10.1016/S0007-8506(07)60625-8
Perng DB, Chen SH, Chang YS (2009) A novel internal thread defect auto-inspection system. Int J Adv Manuf Technol. doi:10.1007/s00170-009-2211-8
Yi S, Haralick RM, Saphiro LG (1995) Optimal sensor and light source positioning for machine vision. Computerv Image Underst 61(1):122–137. doi:10.1006/cviu.1995.1009
Martin D (2007) A practical guide to machine vision lighting. Advanced illumination. http://advancedillumination.com/uploads/downloads/ A Practical Guide to Machine Vision Lighting.pdf. Accessed 30 Jan 2009
Noda N, Kamimura S (2008) A new microscope optics for laser dark-field illumination applied to high precision two dimensional measurement of specimen displacement. Rev Sci Instrum 79(2):1–7. doi:10.1063/1.2839914
Bamforth PE, Jackson MR, Williams K (2007) Transmission dark-field illumination method for high-accuracy automatic lace scalloping. Int J Adv Manuf 32(5–6):599–607. doi:10.1007/s00170-005-0359-4
Biss DP, Youngworth KS, Brown TG (2006) Dark-field imaging with cylindrical-vector beams. Appl Opt 45(3):470–479. doi:10.1364/AO.45.000470
Thomas K (2003) Image processing with LabVIEW™ and IMAQ™ Vision. Prentice-Hall, Englewood Cliffs
Juran JM, Godfrey AB (1998) Juran's quality control handbook, 5th edn. McGraw-Hill, New York. doi:10.1036/007034003X
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Boby, R.A., Sonakar, P.S., Singaperumal, M. et al. Identification of defects on highly reflective ring components and analysis using machine vision. Int J Adv Manuf Technol 52, 217–233 (2011). https://doi.org/10.1007/s00170-010-2730-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-010-2730-3