Biometric person identification systems identify individuals using personal characteristics such as fingerprints, eyes or facial recognition. However, in some critical situations, such as fires, serious traffic accidents, earthquakes or serious injuries, these features can become ineffective. In certain situations, dental characteristics may become the only valid biometric feature for identification. In these cases, forensic dentists work by examining dental structures to establish a person's identity. Currently, studies are being carried out to develop an automated recognition system based on computer vision to assist forensic dentists. However, due to the difficulties in processing panoramic X-ray images and challenges in accessing the data, person matching studies with these images are limited. This paper presents a novel method for matching people based on panoramic X-ray images. Dental person recognition studies can proceed either by investigating the similarity of teeth or by examining the similarity of jaws. In this work, a new approach that uses keypoint descriptors to perform tooth-jaw matching is proposed. This approach offers a high match rate by allowing to search for dental features on a jaw-by-jaw basis and requires less computational complexity than tooth-to-tooth matching. Unlike jaw-to-jaw approaches, it is possible to match individual teeth. The method presented in this study provides a novel approach with significant matching accuracy and efficiency. By evaluating the effectiveness of these methods on panoramic images, the study contributes to forensic dental identification methods in scenarios where traditional biometric features may fall short.