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dc.contributor.advisorUddin, Dr. Jia
dc.contributor.authorFahad, Salem Quddus
dc.contributor.authorHasan, Md. Nazmul
dc.contributor.authorSultana, Sharmin
dc.contributor.authorRabbani, Golam Shams
dc.date.accessioned2018-02-15T09:46:03Z
dc.date.available2018-02-15T09:46:03Z
dc.date.issued2017-12
dc.identifier.otherID 12201038
dc.identifier.otherID 13101177
dc.identifier.otherID 13101187
dc.identifier.otherID 13101171
dc.identifier.urihttp://hdl.handle.net/10361/9485
dc.descriptionThis thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (pages 29-31).
dc.description.abstractDental biometrics is a very important feature in human identification. It can help greatly in Forensic Dentistry. In this paper, we present a method for identifying people based on shapes and appearances of their teeth using Edge detection, pixel value counting and feature extraction. This method automatically detects important features to identify a person. Wiener filter is used to reduce noise and provide a smooth image. For edge detection, we have used Canny Edge Detection algorithm where preprocessed filtered grey scale image's edge has been defined through Gaussian filtering and Edge thresholding. From the given edge detected image canny method determines the region of shape which represents binary pixel value. This pixel value can be used in image identification. Furthermore, the SURF algorithm used to define interest points. Given a query image (i.e., Postmortem radiograph), each tooth is matched with the archived teeth in the database (Antemortem radiographs). Our goal of using appearance and shape-based features together is to overcome the drawback of using only the contour of the tooth, which can be strongly affected by the quality of the images. The experimental results are based on a database of 20 panoramic x ray images show that our method is effective in identifying individuals based on their dental radiographs.en_US
dc.description.statementofresponsibilitySalem Quddus Fahad
dc.description.statementofresponsibilityMd. Nazmul Hasan
dc.description.statementofresponsibilitySharmin Sultana
dc.description.statementofresponsibilityGolam Shams Rabbani
dc.format.extent31 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectEdge detectionen_US
dc.subjectPixel valueen_US
dc.subjectSURF algorithmen_US
dc.subjectFeature extractionen_US
dc.subjectDental radiographen_US
dc.subjectHuman identificationen_US
dc.subjectDental biometricsen_US
dc.titleHuman identification using dental radiographen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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