Biometrics- Dental Radiograph Segmentation using Clustering Algorithm

Authors : P. Ramprasad, Syed Asif Basha, G. R. Pradumna

Abstract: Biometrics is the science of establishing the identity of an individual based on the physical, chemical or behavioral attributes of the person. The relevance of biometrics in modern society has been reinforced by the need for large scale identity management systems whose functionality relies on the accurate determination of an individual’s identity. Digital Image Processing is one of the contenders in the field of biometrics. Segmentation is one of the leading areas of research activities under Image Processing and cluster analysis is the mandatory knowledge required for segmentation. Proposed work aims at this. Cluster analysis can be done using various clustering algorithms but widely used algorithm is K-means clustering algorithm. The interesting fact is that even though the researchers are working on this algorithm for past 20 years still there are many things need to be changed such as time and memory. The proposed work focuses on dental radiograph segmentation using the above said algorithm. Using this algorithm radiograph can be segmented depending upon the requirements like , contours, cavities and the pattern of the teeth. Algorithm can be used for Antemortem (AM) and Postmortem (PM) applications used in Advanced Dental Identification Systems (ADIS). Index Terms: ADS, MD, ID/IP, Monitor

Keywords : Biometrics, Clustering, Dental radiographs, Segmentation.