A Preprocessing Method for Fragment Perforation Image Detection

The perforation data left by the fragments generated by the explosion of ammunition warheads on the surrounding metal plates can reflect the dispersion characteristics of the fragments, which is a commonly used ammunition power testing method. Using image detection based methods to analyze metal plate perforation images can quickly and accurately detect the number and size of fragment perforation. Therefore, image quality is crucial for the accuracy of the analysis results. This study proposes an image preprocessing method for detecting metal plate perforation images, and compares and analyzes the effects of different filtering methods, morphological processing methods, and perforation edge detection methods on the image preprocessing results, The results show that using median filtering, open operation morphological processing methods, and edge detection methods based on Gaussian fitting models can obtain preprocessed images that better reflect the true bullet hole information.