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GC Snakes: An Efficient and Robust Segmentation Model for Hot Forging Images.
1School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel, Switzerland)
|August 10, 2024
Summary
This study introduces Geometric Continuity Snakes (GC Snakes), an improved active contour model for robustly segmenting hot forging images. GC Snakes enhance geometric parameter measurement accuracy for industrial applications.
Area of Science:
- Computer Vision
- Industrial Metrology
- Materials Science
Background:
- Accurate non-contact measurement of hot forgings is crucial for quality control.
- Image segmentation of forging images is challenging due to varying conditions, impacting performance and robustness.
Purpose of the Study:
- To propose an efficient and robust active contour model for segmenting hot forging images.
- To improve the accuracy and reliability of geometric parameter measurement for hot forgings.
Main Methods:
- Development of a novel active contour model named Geometric Continuity Snakes (GC Snakes).
- Definition of three continuity parameters based on grayscale surface geometry.
- Proposal of a new image force and external energy functional for GC Snakes.
- Introduction of a strategy for generating initial control points for GC Snakes.
Main Results:
- GC Snakes demonstrate superior segmentation performance over existing models for forging images of varying temperatures and sizes.
- The proposed method achieves maximum positioning and dimension errors of 0.5525 mm and 0.3868 mm, respectively.
- GC Snakes offer improved robustness and efficiency in geometric parameter measurement.
Conclusions:
- The GC Snakes model provides a significant advancement in segmenting hot forging images.
- This approach enhances the precision and reliability of non-contact metrology in industrial forging processes.
