EBTM: An Enumeration-Based Thresholding Method for Degraded Circular Dot Segmentation

Circular dots are widely used in various measurement applications due to their inherent symmetry, ease of detection, and scalability. However, when degraded by factors such as specular highlights, low contrast, strong noise, or friction damage, accurately extracting them from the background becomes a significant challenge. To address this issue, an enumeration-based thresholding method (EBTM) is proposed for degraded circular dot segmentation. Firstly, a series of candidate outputs are generated using an enumeration-based thresholding scheme. Next, an assessment criterion is developed to evaluate these candidate outputs. Finally, the optimal segments are selected from each candidate output and combined to produce a reasonable thresholding result. Unlike traditional methods, the novel approach does not focus on selecting the optimal threshold values, but instead aims to choose the best segments to produce the desired output. Owing to the enumeration-based thresholding mechanism, the novel approach demonstrates greater robustness in handling the challenges in degraded circular dot images. Extensive comparative studies demonstrate the superiority of the novel approach.