A novel method of human identification based on dental impression image

•We propose a human identification method based on dental impression images. First, we extract a geometric feature called the calibrated offset distance to describe the dental arch. The dental arch is a distinctive feature of individual teeth. To address the challenges in describing the dental arch, this paper introduces a novel calibrated offset distance that captures the characteristics of the arc, changes in radian, and distances between arc breakpoints simultaneously.•We propose an adaptive threshold strategy for the tooth print detection model based on the YOLOv8 network. We design a gradient training strategy to achieve a robust detection model. Building upon its high positioning accuracy, we propose an adaptive threshold strategy to further enhance the detection accuracy.•We propose a multi-scale and multi-dimensional tooth print aggregation feature. In order to enhance the ability to recognize individuals with similar teeth structures, we further integrate SIFT features to provide a detailed description based on geometric features. This aggregation feature is composed to improve the performance of human identification.