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Dental age estimation is applied in various clinical and scientific disciplines such as pediatric dentistry, orthodontics, archaeology, palaeontology and forensic dentistry. Dental age assessment, particularly in forensic dentistry application for the purpose of human identification, has led to the fastest and cheapest procedure in the estimation process of the undocumented and unrecognized individuals. Traditionally, dental age assessment is done by applying the scoring system based on tooth development from the x-ray image. However, this method can be intricate and time consuming for massive incidents that involve a large number of victims such as a natural disaster. Thus, a number of experts are required during the identification process. Therefore, in this research, the application of digital image processing techniques is used to perform the segmentation and classification of the first molar tooth in every stage of its development. A region-based segmentation method known as Watershed Transform associated with several image enhancement algorithms is implemented. A marker image is automatically computed to control the operation of a watershed transform. Features are extracted based on the area of a segmented tooth, size of crown, the distance of left crown to root and distance of right crown to root. As a result, 94% and 92.8% of segmentation and classification accuracy are obtained.

Region-based segmentation and classification of Mandibular First Molar Tooth based on Demirjian’s method