A new feature extraction method from dental X-ray images for human identification

Using dental radiography is an alternative approach to identify a deceased person, especially in cases that other biometric traits cannot be handled. This paper proposes a new method for feature extraction from dental radiography images to identify people. First, dental works are segmented in the X-ray images using image processing techniques. Then, radius vector function and support function are extracted for each segmented region. These functions are independent of image translation. The presented algorithm modifies both functions to be invariant under image rotation as well. Also, by normalizing the functions, the problems due to image scale variations can be solved. Image translation, rotation and scale variations are basic challenges when dental features are compared in spatial domain. Experiments prove suitable recognition accuracy in the proposed approach which does not require teeth alignment at the matching level.