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DENTAL BIOMETRICS HUMAN IDENTIFICATION BASED ON DENTAL WORK INFORMATION

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dc.contributor.author DR SHOAB AHMED KHAN, TAIMUR MEHMOOD, ZEESHAN ZAFAR,BILAL BHATTI, DR USMAN AKRAM
dc.date.accessioned 2025-04-29T04:10:54Z
dc.date.available 2025-04-29T04:10:54Z
dc.date.issued 2014
dc.identifier.other DE-COMP-32
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/52591
dc.description SUPERVISOR Dr. Shoab Ahmed Khan Dr. Usman Akram en_US
dc.description.abstract Dental biometrics is used in the forensic odontology to identify individuals based on their dental characteristics. Forensic odontology is a branch of forensic medicine that deals with teeth and marks left by teeth (as in identifying criminal suspects or the remains of a dead person). In this project, we have designed a system for person identification using dental data. The system used two types of dental images for person identification i.e. dental radiographs and colored dental images. The radiograph dataset consists of antemortem and post-mortem radiographs of same person. For radiograph images, the implemented system first extracts a single tooth manually from dental radiograph and then performs binarization using adaptive thresholding. The horizontal and vertical profiles are extracted along with the orientation of tooth as features to construct a feature vector. The post-martem images are used for matching purpose which is based on simple distance based matching. For colored dental images, HSV and LAB color spaces are used and teeth are extracting by using k-means clustering. The system applies morphological operations as post processing steps to remove undesirable regions. The feature vector consists of mean, min and max saturation values, Euler number and area. Matching is again performed using distance between training and test feature vectors. The validity of implemented system is tested using accuracy (identification rate) which is the ratio of correctly matched images to total number of images in dataset. Keywords: dental biometrics, biometrics, forensic odontology, dental radiograph, k means clustering, distance based matching en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.title DENTAL BIOMETRICS HUMAN IDENTIFICATION BASED ON DENTAL WORK INFORMATION en_US
dc.type Project Report en_US


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