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A rotation invariant template matching algorithm based on Sub-NCC.

Yifan Zhang1, Zhi Zhang2, Shaohu Peng1

  • 1School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511400, China.

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|August 9, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a faster template matching method using Sub-Normalized Cross Correlation (Sub-NCC) for rotated images. The technique achieves over 95% accuracy and rapid matching times under 0.1 seconds.

Keywords:
machine visionnormalized cross correlationrotation invariancestable pixelstemplate matching

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Area of Science:

  • Computer Vision
  • Image Processing
  • Pattern Recognition

Background:

  • Traditional template matching methods, such as Normalized Cross Correlation (NCC), are computationally intensive and slow when applied to rotated images.
  • The need for efficient and accurate image matching algorithms is critical in various applications, including robotics, medical imaging, and surveillance.

Purpose of the Study:

  • To develop an anti-rotation template matching method that significantly improves speed and maintains high accuracy.
  • To enhance the robustness and anti-jamming capabilities of template matching algorithms.

Main Methods:

  • A novel template matching approach based on a portion of pixels, termed Sub-Normalized Cross Correlation (Sub-NCC), is proposed.
  • Rotation-invariant edge points are selected from rotation-invariant pixels for efficient rough matching, quickly eliminating non-matching regions.
  • Appropriate pyramid series and thresholds are utilized for optimizing performance on large-scale search maps.

Main Results:

  • The proposed Sub-NCC method demonstrates improved anti-jamming capabilities compared to standard NCC.
  • Experimental results show an accuracy rate exceeding 95% for the anti-rotation template matching.
  • Matching time for a 300,000-pixel search map at any angle is controlled within 0.1 seconds.

Conclusions:

  • The developed anti-rotation template matching method offers a significant speed improvement over traditional techniques.
  • The Sub-NCC approach provides a robust and accurate solution for template matching in the presence of image rotation.
  • This method is highly efficient for real-time applications involving large images and arbitrary rotations.