Multimedia Tools and Applications

, Volume 76, Issue 2, pp 2495–2513 | Cite as

A new computer vision based multi-indentation inspection system for ceramics

  • Junxiang Wang
  • Ying Liu
  • Dong Zhang
  • Huacang Peng
  • Yonghong Zhu
Article

Abstract

Ceramic has been one of most important daily used items since ancient ages. As the worldwide ceramic production grows, the quality evaluation for ceramics comes into a critical task for silicate industry. Automatic evaluation of ceramic shape has the potential to improve the ceramic product quality and production efficiency. This paper proposes an online automatic inspection system and a new algorithm for defect detection and feature analysis based on computer vision technology. The hardware module of the proposed system is designed to transport ceramic products in a suitable speed, acquire images of products, and perform intelligent control. The software module of the systems detects ceramic outline and evaluates the size of defects from the acquired product images. Experimental results show the efficiency and accuracy of the proposed system.

Keywords

Indentation defect Ceramic roundness Multi-indentation detection Computer vision 

Notes

Acknowledgments

This work is supported by the National Science Foundation of China (61402209, 61100170, 61164014 and 61563022), Invention Patent Industrialization Demonstration Project of Jiangxi Province (20143BBM26113) and the CICAEET fund and the PAPD fund.

References

  1. 1.
    Amenabar I, Lopez F, Mendikute A (2013). In introductory review to the non-destructive testing of composite mater. 34(6):152–169Google Scholar
  2. 2.
    Amenabara I, Mendikutea A, López-Arraizaa A, Lizaranzub M, Aurrekoetxeac J (2011) Comparison and analysis of non-destructive testing techniques suitable for delamination inspection in wind turbine blades. Compos Part B 42(5):1298–1305CrossRefGoogle Scholar
  3. 3.
    Anton SR, Erturk A, Inman D (2012) Bending strength of piezoelectric ceramics and single crystals for multifunctional load-bearing applications. IEEE Trans Ultrason Ferroelectr Freq Control 59(6):1085–1092CrossRefGoogle Scholar
  4. 4.
    Can W, Sheng XB, Fa HM (2015) The rapid precision evaluation of roundness based on area hunting. Manuf Autom 37(6):94–96Google Scholar
  5. 5.
    Chan FWY (2009) Measurement sensitivity enhancement by improved reflective computer vision technique for non-destructive evaluation. NDT E Int 43(3):210–215CrossRefGoogle Scholar
  6. 6.
    Chotard T, Gimet-Breart N, Smith A, Fargeot D, Bonnet JP, Gault C (2001) Application of ultrasonic testing to describe the hydration of calcium aluminate cement at the early age. Cem Concr Res 31(3):405–412CrossRefGoogle Scholar
  7. 7.
    Courtney P, Böttcher P (2003) ECVision White paper on industrial applications of cognitive visionGoogle Scholar
  8. 8.
    Forsyth D, Yolken H, Matzkanin G (2006) A brief introduction to non-destructive techniques. AMMTIAC Quart 1(2):7–10Google Scholar
  9. 9.
    Greminger MA, Nelson BJ (2004) Vision-based force measurement. IEEE Trans Pattern Anal Mach Intell 26(3):290–298CrossRefGoogle Scholar
  10. 10.
    Hu X (2007) ARM9-based roundness embedded measurement system for daily-used ceramic. Master thesis, Jingdezhen Ceramic InstituteGoogle Scholar
  11. 11.
    Huang Q, Bando Y, Xu X, Nishimura T, Zhi C, Tang CC, Xu FF, Gao L, Golberg D (2007) Enhancing superplasticity of engineering ceramics by introducing BN nanotubes. Nanotechnology 18(48):485706–485707CrossRefGoogle Scholar
  12. 12.
    Jasinien E, Raiutis R, Literis R, Voleiis A, Vladiauskas A, Mitchard D, Amos M (2009) NDT of wind turbine blades using adapted ultrasonic and radiographic techniques. Nondestruct Test Cond Monit 51(9):477–483CrossRefGoogle Scholar
  13. 13.
    Javier GM, Jaime GG, Ernesto VS (2011) Non-destructive techniques based on eddy current testing. Sensors 11(3):2525–2565CrossRefGoogle Scholar
  14. 14.
    Kalinichenko NP, Kalinichenko AN, Konareva IS (2011) Reference specimens of nonmetallic materials for penetrant nondestructive testing. Russ J Nondestruct Test 47(10):663–666CrossRefGoogle Scholar
  15. 15.
    Kasaia N, Takadaa A, Fukuokab K, Aiyamac H, Hashimotod M (2011) Quantitative investigation of a standard test shim for magnetic particle testing. NDT E Int 44(5):421–426CrossRefGoogle Scholar
  16. 16.
    Leta FR, Feliciano FF, Souza ILD, Cataldo E (2006) Discussing accuracy in an automatic measurement system using computer vision techniques. Int Congr Mech Eng 2(1):645–652Google Scholar
  17. 17.
    Momono T, Noda B (1999) Sound and vibration in rolling bearings. Motion Control 6(2):29–37Google Scholar
  18. 18.
    Oda I, Otani Y, Liu L, Yoshizawa T (1998) Vibration detection using moving grating technique in photorefractive two-wave mixing. Jpn J Appl Phys 37(6A):3304–3308CrossRefGoogle Scholar
  19. 19.
    Pernera P, Zscherpelb U, Jacobsenb C (2000) A comparison between neural networks and decision trees based on data from industrial radiographic testing. Pattern Recogn Lett 22(1):47–54CrossRefGoogle Scholar
  20. 20.
    Pratt V (1987) Direct least-squares fitting of algebraic surfaces. Comput Graph 21(1):145–152MathSciNetCrossRefGoogle Scholar
  21. 21.
    Xiong W, Zhan W, Dong HL (2008) China’s architectural ceramics open up countermeasures international markets. China Ceram 44(8):1001–1005Google Scholar
  22. 22.
    Xia Z, Wang X, Sun X, Liu Q, Xiong N (2014) Steganalysis of LSB matching using differences between nonadjacent pixels. Multimedia Tools and Applications 1(16):1–16Google Scholar
  23. 23.
    Li J, Li X, Yang B, Sun X (2015) Segmentation-based Image Copy-move Forgery Detection Scheme. IEEE Trans Inf Forensics Secur 10(3):507–518Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Junxiang Wang
    • 1
    • 2
  • Ying Liu
    • 1
  • Dong Zhang
    • 3
  • Huacang Peng
    • 1
  • Yonghong Zhu
    • 1
  1. 1.School of Mechanical and Electronic EngineeringJingdezhen Ceramic InstituteJiangxiChina
  2. 2.School of computer and softwareNanjing University of Information Science & TechnologyNanjingChina
  3. 3.School of Information Science and TechnologySun Yat-sen UniversityGuangdongChina

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