Overview
This study applies edge-based image analysis within a computer vision framework to classify necrophagous species of Chrysomya spp. In forensic entomology, species identification traditionally relies on morphological characteristics of the cephalopharyngeal skeleton and related structures. This research digitizes and analyzes edge features of the cephalopharyngeal skeleton to develop an automated classification system for selected forensic Chrysomya species. The expected outcome is a reproducible computational tool for species discrimination, with potential applications in anomaly detection and quality control in forensic casework.