Distortion Invariant Object Recognition Based on Mach-Zehnder Joint Transform Correlation in YIQ Colour Space

Authors

  • Chulung Chen Electrical Engineering Yuan Ze University
  • Kaining Gu Department of Electrical Engineering, Yuan Ze University, Taiwan;
  • Jianshuen Fang Department of Electrical Engineering, Yuan Ze University, Taiwan;
  • hungcheng Lee Department of Electrical Engineering, Yuan Ze University, Taiwan;

DOI:

https://doi.org/10.14738/aivp.71.5965

Keywords:

Joint transform correlation, Colour pattern recognition

Abstract

We investigate the YIQ colour space in conjunction with average cross correlation optimization algorithm to design the reference function for pattern recognition on various views of the interested colour object. Joint transform correlation is devoted for recognition of colour targets. The  reference function for each color channel is trained with true class images rotated in-plane at 2 degrees intervals between -14 degrees and 14 degrees. Results indicates the feasibility of our proposed method.

Author Biography

Chulung Chen, Electrical Engineering Yuan Ze University

Professor
Electrical Engineering

References

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Published

2019-03-09

How to Cite

Chen, C., Gu, K., Fang, J., & Lee, hungcheng. (2019). Distortion Invariant Object Recognition Based on Mach-Zehnder Joint Transform Correlation in YIQ Colour Space. European Journal of Applied Sciences, 7(1), 13. https://doi.org/10.14738/aivp.71.5965