Skip to main content
SpringerLink
Log in

A Novel Blemish Detection Algorithm for Camera Quality Testing

  • Conference paper
  • First Online:
Knowledge Science, Engineering and Management (KSEM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10412))

  • 1920 Accesses

Abstract

In the camera manufacturing, there exist dusts, fingerprints, and water spots on the image sensor and lens. Hence, the resultant effects of darker region is called blemish, which causes a significant reduction in camera quality. The shapes of blemishes are diverse and irregular. Traditional method detects blemishes using image median filtering in a single direction which leads to false alarm and mis-detection for images with high level of noises. Thus, we present a novel filtering method for blemish detection, which utilizes four directional filters in the 0, 45, 90, 135 degrees directions. Compared to the conventional single direction filter, the multidirectional filters take into account more spatial information to more accurately detect blemishes for both weak and strong blemishes. Moreover, the proposed method uses a new adaptive threshold to better accommodate different image noise levels automatically. Experimental results on two batches of production samples (600 images) show the effectiveness of the proposed method over the conventional method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Cazier, R., Voss, S.D., Yost, J.: Blemish detection and notification in an image capture device. United States Patent No. 8982262 B2 (2015)

    Google Scholar 

  2. Kim, S., Kang, T., Jeong, D.: Region mura detection using efficient high pass filtering based on fast average operation. In: Proceedings of the 17th World Congress, International Federation of Automatic Control, vol. 17 (2008)

    Google Scholar 

  3. Lin, H.D., Chiu, Y.S.P.: Computer-aided quality system for visual blemish inspection of epoxy packages. Sci. Iranica 18, 1591–1599 (2011)

    Article  Google Scholar 

  4. Pietikainen, M., Ojala, T., Silven, O.: Approaches to texture-based classification, segmentation and surface inspection. In: Handbook of Pattern Recognition and Computer Vision, pp. 711–736 (1999)

    Google Scholar 

  5. Tsai, D.M., Chuang, S.T.: ID-based defect detection in patterned TFT-LCD panels using characteristic fractal dimension and correlations. Mach. Vis. Appl. 20, 423–434 (2009)

    Article  Google Scholar 

  6. Lin, H.-D., Chung, C.-Y., Chiu, S.W.: Computer-aided vision system for surface blemish detection of LED chips. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds.) ICANNGA 2007. LNCS, vol. 4432, pp. 525–533. Springer, Heidelberg (2007). doi:10.1007/978-3-540-71629-7_59

    Chapter  Google Scholar 

  7. Chiu, Y.S., Lin, H.D.: An innovative blemish detection system for curved LED lenses. Expert Syst. Appl. 40, 471–479 (2013)

    Article  Google Scholar 

  8. Pratt, W.K., Sawkar, S.S., O’Reilly, K.: Automatic blemish detection in liquid crystal flat panel displays. In: Proceedings of SPIE-The International Society (1998)

    Google Scholar 

  9. Reza, M.T.: Vignetting artifact reduction in an efficient way for digital camera image. Tampere University of Technology (2008)

    Google Scholar 

  10. Zhang, H., Shen, S., McAllister, I.A.: Camera blemish defects detection. United States Patent No. 8797429 B2 (2013)

    Google Scholar 

  11. Lepisto, L., Nikkanen, J., Suksi, M.: Blemish detection in camera production testing using fast difference filtering. J. Electron. Imaging 18, 020501 (2009)

    Article  Google Scholar 

  12. Boncelet, C., Bovik, A.C.: Handbook of Image and Video Processing. Academic Press, Cambridge (2005)

    Google Scholar 

Download references

Acknowledgments

This work was supported in part by the Shenzhen Emerging Industries of the Strategic Basic Research Project (No. JCYJ20160226191842793), and the National Natural Science Foundation of China (No. 61602312, 61602314, 61620106008).

Author information

Authors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong Province, China

    Kun Wang, Kwok-Wai Hung & Jianmin Jiang

Authors
  1. Kun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kwok-Wai Hung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jianmin Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kwok-Wai Hung .

Editor information

Editors and Affiliations

  1. Deakin University, Burwood, Victoria, Australia

    Gang Li

  2. University of Arizona, Tucson, Arizona, USA

    Yong Ge

  3. Southwest University, Chongqing, China

    Zili Zhang

  4. Peking University, Beijing, China

    Zhi Jin

  5. University of Technology Sydney, Sydney, New South Wales, Australia

    Michael Blumenstein

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Wang, K., Hung, KW., Jiang, J. (2017). A Novel Blemish Detection Algorithm for Camera Quality Testing. In: Li, G., Ge, Y., Zhang, Z., Jin, Z., Blumenstein, M. (eds) Knowledge Science, Engineering and Management. KSEM 2017. Lecture Notes in Computer Science(), vol 10412. Springer, Cham. https://doi.org/10.1007/978-3-319-63558-3_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-63558-3_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63557-6

  • Online ISBN: 978-3-319-63558-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation