Novel approaches to determine age and gender from dental x-ray images by using multiplayer perceptron neural networks and image processing techniques

Abstract It may be necessary to determine the identity or gender of a person for any reason (disasters, inheritance etc.). In such cases, forensic medical institutions are asked for help. Forensic science institutions try to estimate the age of people's teeth and bones. In this study, a novel algorithm was developed to keep these predictions at the highest level and to obtain definite results. The data base of 162 different tooth classes is created manually. All image sizes are 150×150 pixels. First, image preprocessing techniques have been applied to teeth images. These preprocessing techniques were first applied to teeth images. After this process, the segmentation process of the teeth images was performed to extract the feature by novel segmentation algorithm. Segmentation can be done automatically and dynamically. Numerical data obtained as a result of feature extraction from dental images is presented as an inputs to Multi layer perceptron neural network. In application, feature reduction can be performed. Thanks to the originally developed algorithm, the highest success rates were obtained with the highest 99.9% (full segment) and 100% (notfull segment) classification. After classification, for many dental groups the age estimate is performed with zero error. Application was developed as a multidisciplinary study.