Glass Detection for Digital Forensics Using Unsupervised Clustering Algorithm | Original Article
In many studies attempting to segment various types of populations, the Fuzzy C-means (FCM) algorithm has been found to be one of the most effective algorithms, and it can thus be used to assist forensic experts in identifying different types of glasses discovered at a crime scene. This paper suggests a method for creating clusters of different types of glasses from their properties that is based on the FCM algorithm. The proposed method aims to create clusters based on various factors such as refractive index and composition. New values can be plotted on the graph after clusters have formed, and the type of glass located at the crime scene can be calculated depending on the orientation of the projection.