COMPUTATION OF IMAGE DISTANCES FOR HUMAN IDENTIFICATION IN DENTAL RADIOGRAPHS

Dental radiographs are used for human identification in dental biometrics. The dental radiograph gives us various information such as tooth contours, relative positions of neighbouring teeth, and shapes of the dental work (e.g., crowns, fillings, and bridges). The proposed system has 2 stages namely (1) Feature Extraction and (2) Matching. In feature extraction, active contour model is used to extract the contour. The matching stage has 2 steps viz. Computation of Image distances and Subject identification. In tooth level matching tooth contours are matched using “Shape registration Method” and depending upon the overlapping areas the dental works are matched. Then the values of the distance between the tooth contours and dental works are combined using posterior probabilities. Tooth correspondence between query radiograph and database radiograph are established. Distance between the teeth are used to calculate the similarity between the two radiographs. Finally the distance between the radiographs provide the details about the subject associated with these radiographs. The dataset contains 10 normal images and 55 OPG images which was collected from Madura Dental Hospital. The accuracy of the algorithm is measured by the ratio of Correct Detection images to Total No of images. The experimental results show that this proposed algorithm is accurate about 72%.