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CHMM Object Detection Based on Polygon Contour Features by PSM.

Shufang Zhuo1, Yanwei Huang2

  • 1College of Automation Engineering, Fujian Polytechnic of Information Technology, Fuzhou 350003, China.

Sensors (Basel, Switzerland)
|September 9, 2022
PubMed
Summary
This summary is machine-generated.

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This study introduces a novel piecewise split-merge polygon approximation for object contour extraction. The method enhances robustness to scale variance and improves object detection rates by reducing feature numbers.

Area of Science:

  • Computer Vision
  • Image Processing
  • Pattern Recognition

Background:

  • Conventional split-merge algorithms exhibit sensitivity to object scale variations and splitting initiation points.
  • Accurate object contour feature extraction is crucial for reliable object detection.

Purpose of the Study:

  • To propose a piecewise split-merge polygon approximation method for robust object contour feature extraction.
  • To enhance object detection accuracy by addressing limitations of existing contour-based methods.

Main Methods:

  • Contour corners are utilized as starting points for piecewise approximation, mitigating starting point sensitivity.
  • The split-merge algorithm is applied to individual contour segments for polygon approximation.
  • Distance ratio and arc length ratio are employed as iterative stopping criteria, improving scale variance robustness.
Keywords:
Coupled Hidden Markov Modelcontourobject detectionpiecewise split–merge algorithmpolygonal approximation

Related Experiment Videos

  • A Coupled Hidden Markov Model integrates contour angle and length features for object detection.

    • Main Results:

    • The proposed algorithm demonstrates improved robustness to object scale variance.
    • It effectively reduces the number of contour features required for detection.
    • The method achieves a higher object detection rate compared to existing contour-based algorithms.
    • Validation on ETHZ Shape Classes and INRIA Horses datasets confirms performance.

    Conclusions:

    • The piecewise split-merge polygon approximation offers a more robust and efficient approach to object contour feature extraction.
    • Combining contour angle and length within a Coupled Hidden Markov Model enhances object detection accuracy.
    • This method presents a significant advancement in contour-based object detection techniques.