Skip to main content

Advertisement

SpringerLink
Log in

A Method to Measure the Bracelet Based on Feature Energy

  • Original Paper
  • Published:
Sensing and Imaging Aims and scope Submit manuscript

Abstract

To measure the bracelet automatically, a novel method based on feature energy is proposed. Firstly, the morphological method is utilized to preprocess the image, and the contour consisting of a concentric circle is extracted. Then, a feature energy function, which is relevant to the distances from one pixel to the edge points, is defined taking into account the geometric properties of the concentric circle. The input image is subsequently transformed to the feature energy distribution map (FEDM) by computing the feature energy of each pixel. The center of the concentric circle is thus located by detecting the maximum on the FEDM; meanwhile, the radii of the concentric circle are determined according to the feature energy function of the center pixel. Finally, with the use of a calibration template, the internal diameter and thickness of the bracelet are measured. The experimental results show that the proposed method can measure the true sizes of the bracelet accurately with the simplicity, directness and robustness compared to the existing methods.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Mukhopadhyay, P., & Chaudhuri, B. B. (2014). A survey of hough transform. Pattern Recognition, 48(3), 993–1010.

    Article  Google Scholar 

  2. Cao, X., & Deravi, F. (1992). An efficient method for the detection of multiple concentric circles. IEEE International Conference on Acoustics, 3, 137–140.

    Google Scholar 

  3. Silveira, M. (2005). An algorithm for the detection of multiple concentric circles. Lecture Notes in Computer Science, 3523, 143–224.

    Google Scholar 

  4. Qiao, N. S., Ye, Y. T., Mo, C. H., et al. (2010). Method for the detection of concentric circles of photoelectric image of circular hole in printed circuit board. Acta Optica Sinica, 30(1), 75–78.

    Article  Google Scholar 

  5. Yue, G. H., Lu, C. H., Sheng, L. Q., & Liu, Y. N. (2012). A combined method for concentric circles detection in image of o-shape rubber ring. Advanced Materials Research, 488–489, 1619–1623.

    Article  Google Scholar 

  6. Ying, X., & Zha, H. (2007). An efficient method for the detection of projected concentric circles. IEEE International Conference on Image Processing, 6, VI-560–VI-563.

    Google Scholar 

  7. Chen, X., Lu, L., & Gao, Y. (2012). A new concentric circle detection method based on Hough transform. In International conference on computer science and education (pp. 753–758).

  8. Chen, X., Lu, L., & Yang, S. (2014). Concentric circle detection based on normalized distance variance and the straight line Hough transform. IEEE International Conference on Computer Science & Education, 96, e84–e84.

    Google Scholar 

  9. Akinlar, C., & Topal, C. (2013). Edcircles: A real-time circle detector with a false detection control. Pattern Recognition, 46(3), 725–740.

    Article  Google Scholar 

  10. Marco, T. D., Cazzato, D., Leo, M., & Distante, C. (2015). Randomized circle detection with isophotes curvature analysis. Pattern Recognition, 48(2), 411–421.

    Article  Google Scholar 

  11. Yuan, B., & Liu, M. (2015). Power histogram for circle detection on images. Pattern Recognition, 48(10), 3268–3280.

    Article  Google Scholar 

  12. Liu, H. M., & Wang, Z. H. (2013). PLDD: Point-lines distance distribution for detection of arbitrary triangles, regular polygons and circles. Journal of Visual Communication and Image Representation, 25(2), 273–284.

    Article  Google Scholar 

  13. Scitovski, R., & Marošević, T. (2015). Multiple circle detection based on center-based clustering. Pattern Recognition Letters, 52, 9–16.

    Article  MATH  Google Scholar 

  14. Liu, D., Wang, Y., Tang, Z., & Lu, X. (2015). A robust circle detection algorithm based on top-down least-square fitting analysis. Optics Communications, 343(4), 66–72.

    Article  Google Scholar 

  15. Cai, J., Huang, P., Chen, L., & Zhang, B. (2016). An efficient circle detector not relying on edge detection. Advances in Space Research, 57(11), 2359–2375.

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (61572173, 61472119 and 61472373), the program for Science and Technology Innovation Talents in Universities of Henan Province (13HASTIT039), Henan Polytechnic University Innovative Research Team (T2014-3) and Henan Polytechnic University Fund for Distinguished Young Scholars (J2016-3).

Author information

Authors and Affiliations

  1. School of Computer Science and Technique, Henan Polytechnic University, Jiaozuo, 454000, China

    Hongmin Liu, Lu Li, Zhiheng Wang & Zhanqiang Huo

Authors
  1. Hongmin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhiheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhanqiang Huo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhiheng Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, H., Li, L., Wang, Z. et al. A Method to Measure the Bracelet Based on Feature Energy. Sens Imaging 18, 14 (2017). https://doi.org/10.1007/s11220-017-0163-x

Download citation

  • Received:

  • Revised:

  • Published:

  • DOI: https://doi.org/10.1007/s11220-017-0163-x

Keywords

Search

Navigation