# GC Snakes: An Efficient and Robust Segmentation Model for Hot Forging Images

## TL;DR

This paper introduces GC Snakes, a new image segmentation model for hot forging images that improves accuracy and efficiency in measuring geometric parameters.

## Contribution

The novel GC Snakes model uses geometric continuity parameters and an improved active contour approach for robust segmentation of hot forging images.

## Key findings

- GC Snakes outperforms existing models in segmentation accuracy for forging images of varying temperatures and sizes.
- The maximum positioning and dimension errors achieved by GC Snakes are 0.5525 mm and 0.3868 mm, respectively.
- The proposed model improves convergence and robustness in grayscale-based image segmentation for hot forging applications.

## Abstract

Machine vision is a desirable non-contact measurement method for hot forgings, as image segmentation has been a challenging issue in performance and robustness resulting from the diversity of working conditions for hot forgings. Thus, this paper proposes an efficient and robust active contour model and corresponding image segmentation approach for forging images, by which verification experiments are conducted to prove the performance of the segmentation method by measuring geometric parameters for forging parts. Specifically, three types of continuity parameters are defined based on the geometric continuity of equivalent grayscale surfaces for forging images; hence, a new image force and external energy functional are proposed to form a new active contour model, Geometric Continuity Snakes (GC Snakes), which is more percipient to the grayscale distribution characteristics of forging images to improve the convergence for active contour robustly; additionally, a generating strategy for initial control points for GC Snakes is proposed to compose an efficient and robust image segmentation approach. The experimental results show that the proposed GC Snakes has better segmentation performance compared with existing active contour models for forging images of different temperatures and sizes, which provides better performance and efficiency in geometric parameter measurement for hot forgings. The maximum positioning and dimension errors by GC Snakes are 0.5525 mm and 0.3868 mm, respectively, compared with errors of 0.7873 mm and 0.6868 mm by the Snakes model.